Built site for AMR@3.0.1.9053: 23beebc

2026-06-01 05:41:46 +02:00 · 2026-04-30 08:07:42 +00:00
parent 425f4ad827
commit 3a3027f171
100 changed files with 742 additions and 649 deletions
--- a/404.html
+++ b/404.html
@@ -31,7 +31,7 @@

    <a class="navbar-brand me-2" href="https://amr-for-r.org/index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/CLAUDE.html
+++ b/CLAUDE.html
@@ -7,7 +7,7 @@

    <a class="navbar-brand me-2" href="index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -73,7 +73,7 @@
 <span><span class="fu">pkgdown</span><span class="fu">::</span><span class="fu"><a href="https://pkgdown.r-lib.org/reference/build_site.html" class="external-link">build_site</a></span><span class="op">(</span><span class="op">)</span></span>
 <span></span>
 <span><span class="co"># Code coverage report</span></span>
-<span><span class="fu">covr</span><span class="fu">::</span><span class="fu"><a href="http://covr.r-lib.org/reference/package_coverage.html" class="external-link">package_coverage</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div>
+<span><span class="fu">covr</span><span class="fu">::</span><span class="fu">package_coverage</span><span class="op">(</span><span class="op">)</span></span></code></pre></div>
 <p>From the shell:</p>
 <div class="sourceCode" id="cb2"><pre class="sourceCode bash"><code class="sourceCode bash"><span id="cb2-1"><a href="#cb2-1" tabindex="-1"></a><span class="co"># CRAN check from parent directory</span></span>
 <span id="cb2-2"><a href="#cb2-2" tabindex="-1"></a><span class="ex">R</span> CMD check AMR</span></code></pre></div>
@@ -92,13 +92,13 @@ _pkgdown.yml    # pkgdown website configuration</code></pre>
 <div class="section level2">
 <h2 id="r-source-file-conventions">R Source File Conventions<a class="anchor" aria-label="anchor" href="#r-source-file-conventions"></a></h2>
 <p><strong>Naming conventions in <code>R/</code>:</strong></p>
-<table class="table"><thead><tr class="header"><th>Prefix/Name</th>
+<table class="table"><thead><tr><th>Prefix/Name</th>
 <th>Purpose</th>
-</tr></thead><tbody><tr class="odd"><td><code>aa_*.R</code></td>
+</tr></thead><tbody><tr><td><code>aa_*.R</code></td>
 <td>Loaded first (helpers, globals, options, package docs)</td>
-</tr><tr class="even"><td><code>zz_deprecated.R</code></td>
+</tr><tr><td><code>zz_deprecated.R</code></td>
 <td>Deprecated function wrappers</td>
-</tr><tr class="odd"><td><code>zzz.R</code></td>
+</tr><tr><td><code>zzz.R</code></td>
 <td>
 <code>.onLoad</code> / <code>.onAttach</code> initialization</td>
 </tr></tbody></table><p><strong>Key source files:</strong></p>
@@ -136,46 +136,46 @@ _pkgdown.yml    # pkgdown website configuration</code></pre>
 <div class="section level2">
 <h2 id="custom-s3-classes">Custom S3 Classes<a class="anchor" aria-label="anchor" href="#custom-s3-classes"></a></h2>
 <p>The package defines five S3 classes with full print/format/plot/vctrs support:</p>
-<table class="table"><thead><tr class="header"><th>Class</th>
+<table class="table"><thead><tr><th>Class</th>
 <th>Created by</th>
 <th>Represents</th>
-</tr></thead><tbody><tr class="odd"><td><code>&lt;mo&gt;</code></td>
+</tr></thead><tbody><tr><td><code>&lt;mo&gt;</code></td>
 <td><code><a href="reference/as.mo.html">as.mo()</a></code></td>
 <td>Microorganism code</td>
-</tr><tr class="even"><td><code>&lt;ab&gt;</code></td>
+</tr><tr><td><code>&lt;ab&gt;</code></td>
 <td><code><a href="reference/as.ab.html">as.ab()</a></code></td>
 <td>Antimicrobial drug code</td>
-</tr><tr class="odd"><td><code>&lt;av&gt;</code></td>
+</tr><tr><td><code>&lt;av&gt;</code></td>
 <td><code><a href="reference/as.av.html">as.av()</a></code></td>
 <td>Antiviral drug code</td>
-</tr><tr class="even"><td><code>&lt;sir&gt;</code></td>
+</tr><tr><td><code>&lt;sir&gt;</code></td>
 <td><code><a href="reference/as.sir.html">as.sir()</a></code></td>
 <td>SIR value (S/I/R/SDD)</td>
-</tr><tr class="odd"><td><code>&lt;mic&gt;</code></td>
+</tr><tr><td><code>&lt;mic&gt;</code></td>
 <td><code><a href="reference/as.mic.html">as.mic()</a></code></td>
 <td>Minimum inhibitory concentration</td>
-</tr><tr class="even"><td><code>&lt;disk&gt;</code></td>
+</tr><tr><td><code>&lt;disk&gt;</code></td>
 <td><code><a href="reference/as.disk.html">as.disk()</a></code></td>
 <td>Disk diffusion diameter</td>
 </tr></tbody></table></div>
 <div class="section level2">
 <h2 id="data-files">Data Files<a class="anchor" aria-label="anchor" href="#data-files"></a></h2>
 <p>Pre-compiled in <code>data/</code> (do not edit directly; regenerate via <code>data-raw/</code> scripts):</p>
-<table class="table"><colgroup><col width="50%"><col width="50%"></colgroup><thead><tr class="header"><th>File</th>
+<table class="table"><colgroup><col width="50%"><col width="50%"></colgroup><thead><tr><th>File</th>
 <th>Contents</th>
-</tr></thead><tbody><tr class="odd"><td><code>microorganisms.rda</code></td>
+</tr></thead><tbody><tr><td><code>microorganisms.rda</code></td>
 <td>~79,000 microbial species with full taxonomy</td>
-</tr><tr class="even"><td><code>antimicrobials.rda</code></td>
+</tr><tr><td><code>antimicrobials.rda</code></td>
 <td>~620 antimicrobial drugs with ATC codes</td>
-</tr><tr class="odd"><td><code>antivirals.rda</code></td>
+</tr><tr><td><code>antivirals.rda</code></td>
 <td>Antiviral drugs</td>
-</tr><tr class="even"><td><code>clinical_breakpoints.rda</code></td>
+</tr><tr><td><code>clinical_breakpoints.rda</code></td>
 <td>EUCAST + CLSI breakpoints (2011–2025)</td>
-</tr><tr class="odd"><td><code>intrinsic_resistant.rda</code></td>
+</tr><tr><td><code>intrinsic_resistant.rda</code></td>
 <td>Intrinsic resistance patterns</td>
-</tr><tr class="even"><td><code>example_isolates.rda</code></td>
+</tr><tr><td><code>example_isolates.rda</code></td>
 <td>Example AMR dataset for documentation/testing</td>
-</tr><tr class="odd"><td><code>WHONET.rda</code></td>
+</tr><tr><td><code>WHONET.rda</code></td>
 <td>Example WHONET-format dataset</td>
 </tr></tbody></table></div>
 <div class="section level2">
--- a/CLAUDE.md
+++ b/CLAUDE.md
@@ -23,6 +23,7 @@ Concentration (MIC) and disk diffusion handling - Multilingual output
 All commands run inside an R session:

 ``` r
+
 # Rebuild documentation (roxygen2 → .Rd files + NAMESPACE)
 devtools::document()

@@ -95,7 +96,7 @@ The package defines five S3 classes with full print/format/plot/vctrs
 support:

 | Class | Created by | Represents |
-|----------|-----------------------------------------------------------|----------------------------------|
+|----|----|----|
 | `<mo>` | [`as.mo()`](https://amr-for-r.org/reference/as.mo.md) | Microorganism code |
 | `<ab>` | [`as.ab()`](https://amr-for-r.org/reference/as.ab.md) | Antimicrobial drug code |
 | `<av>` | [`as.av()`](https://amr-for-r.org/reference/as.av.md) | Antiviral drug code |
@@ -125,6 +126,7 @@ integrations (ggplot2, dplyr, data.table, tidymodels, cli, crayon, etc.)
 are listed in `Suggests` and guarded with:

 ``` r
+
 if (requireNamespace("pkg", quietly = TRUE)) { ... }
 ```

--- a/LICENSE-text.html
+++ b/LICENSE-text.html
@@ -7,7 +7,7 @@

    <a class="navbar-brand me-2" href="index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/articles/AMR.html
+++ b/articles/AMR.html
@@ -30,7 +30,7 @@

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -91,7 +91,7 @@
 website update since they are based on randomly created values and the
 page was written in <a href="https://rmarkdown.rstudio.com/" class="external-link">R
 Markdown</a>. However, the methodology remains unchanged. This page was
-generated on 25 April 2026.</p>
+generated on 30 April 2026.</p>
 <div class="section level2">
 <h2 id="introduction">Introduction<a class="anchor" aria-label="anchor" href="#introduction"></a>
 </h2>
@@ -147,21 +147,21 @@ make the structure of your data generally look like this:</p>
 </tr></thead>
 <tbody>
 <tr class="odd">
-<td align="center">2026-04-25</td>
+<td align="center">2026-04-30</td>
 <td align="center">abcd</td>
 <td align="center">Escherichia coli</td>
 <td align="center">S</td>
 <td align="center">S</td>
 </tr>
 <tr class="even">
-<td align="center">2026-04-25</td>
+<td align="center">2026-04-30</td>
 <td align="center">abcd</td>
 <td align="center">Escherichia coli</td>
 <td align="center">S</td>
 <td align="center">R</td>
 </tr>
 <tr class="odd">
-<td align="center">2026-04-25</td>
+<td align="center">2026-04-30</td>
 <td align="center">efgh</td>
 <td align="center">Escherichia coli</td>
 <td align="center">R</td>
--- a/articles/AMR.md
+++ b/articles/AMR.md
@@ -3,7 +3,7 @@
 **Note:** values on this page will change with every website update
 since they are based on randomly created values and the page was written
 in [R Markdown](https://rmarkdown.rstudio.com/). However, the
-methodology remains unchanged. This page was generated on 25 April 2026.
+methodology remains unchanged. This page was generated on 30 April 2026.

 ## Introduction

@@ -51,9 +51,9 @@ structure of your data generally look like this:

 |    date    | patient_id |        mo        | AMX | CIP |
 |:----------:|:----------:|:----------------:|:---:|:---:|
-| 2026-04-25 |    abcd    | Escherichia coli |  S  |  S  |
-| 2026-04-25 |    abcd    | Escherichia coli |  S  |  R  |
-| 2026-04-25 |    efgh    | Escherichia coli |  R  |  S  |
+| 2026-04-30 |    abcd    | Escherichia coli |  S  |  S  |
+| 2026-04-30 |    abcd    | Escherichia coli |  S  |  R  |
+| 2026-04-30 |    efgh    | Escherichia coli |  R  |  S  |

 ### Needed R packages

@@ -69,6 +69,7 @@ We will also use the `cleaner` package, that can be used for cleaning
 data and creating frequency tables.

 ``` r
+
 library(dplyr)
 library(ggplot2)
 library(AMR)
@@ -81,6 +82,7 @@ The `AMR` package contains a data set `example_isolates_unclean`, which
 might look data that users have extracted from their laboratory systems:

 ``` r
+
 example_isolates_unclean
 #> # A tibble: 3,000 × 8
 #>    patient_id hospital date       bacteria      AMX   AMC   CIP   GEN  
@@ -119,6 +121,7 @@ still human readable. More importantly,
 of input:

 ``` r
+
 as.mo("Klebsiella pneumoniae")
 #> Class <mo>
 #> [1] B_KLBSL_PNMN
@@ -143,6 +146,7 @@ Gram-stain. They all start with `mo_` and they use
 that still any arbitrary user input can be used:

 ``` r
+
 mo_family("K. pneumoniae")
 #> [1] "Enterobacteriaceae"
 mo_genus("K. pneumoniae")
@@ -165,6 +169,7 @@ mo_snomed("K. pneumoniae")
 Now we can thus clean our data:

 ``` r
+
 our_data$bacteria <- as.mo(our_data$bacteria, info = TRUE)
 #> ℹ Retrieved values from the `microorganisms.codes` data set for "ESCCOL",
 #>   "KLEPNE", "STAAUR", and "STRPNE".
@@ -177,6 +182,7 @@ Apparently, there was some uncertainty about the translation to
 taxonomic codes. Let’s check this:

 ``` r
+
 mo_uncertainties()
 #> Matching scores are based on the resemblance between the input and the full
 #> taxonomic name, and the pathogenicity in humans. See `mo_matching_score()`.
@@ -231,6 +237,7 @@ diffusion values, read more about that on the
 For now, we will just clean the SIR columns in our data using dplyr:

 ``` r
+
 # method 1, be explicit about the columns:
 our_data <- our_data %>%
  mutate_at(vars(AMX:GEN), as.sir)
@@ -308,6 +315,7 @@ page.
 The outcome of the function can easily be added to our data:

 ``` r
+
 our_data <- our_data %>%
  mutate(first = first_isolate(info = TRUE))
 #> ℹ Determining first isolates using an episode length of 365 days
@@ -326,6 +334,7 @@ with the [`filter()`](https://dplyr.tidyverse.org/reference/filter.html)
 function, also from the `dplyr` package:

 ``` r
+
 our_data_1st <- our_data %>%
  filter(first == TRUE)
 ```
@@ -333,6 +342,7 @@ our_data_1st <- our_data %>%
 For future use, the above two syntaxes can be shortened:

 ``` r
+
 our_data_1st <- our_data %>%
  filter_first_isolate()
 ```
@@ -340,6 +350,7 @@ our_data_1st <- our_data %>%
 So we end up with 2 724 isolates for analysis. Now our data looks like:

 ``` r
+
 our_data_1st
 #> # A tibble: 2,724 × 9
 #>    patient_id hospital date       bacteria     AMX   AMC   CIP   GEN   first
@@ -366,6 +377,7 @@ gives a good first impression, as it comes with support for the new `mo`
 and `sir` classes that we now have in our data set:

 ``` r
+
 summary(our_data_1st)
 #>      patient_id        hospital         date              bacteria           
 #>  Length   :2724   Length   :2724   Min.   :2011-01-01   Class :mo            
@@ -417,6 +429,7 @@ table with [`count()`](https://amr-for-r.org/reference/count.md) based
 on the name of the microorganisms:

 ``` r
+
 our_data %>%
  count(mo_name(bacteria), sort = TRUE)
 #> # A tibble: 4 × 2
@@ -445,6 +458,7 @@ columns based on the antibiotic class that your antibiotic results are
 in:

 ``` r
+
 our_data_1st %>%
  select(date, aminoglycosides())
 #> ℹ For `aminoglycosides()` using column GEN
@@ -590,6 +604,7 @@ function to create any of the above antibiogram types. For starters,
 this is what the included `example_isolates` data set looks like:

 ``` r
+
 example_isolates
 #> # A tibble: 2,000 × 46
 #>    date       patient   age gender ward     mo           PEN   OXA   FLC   AMX  
@@ -622,6 +637,7 @@ function supports any (combination) of the previously mentioned
 antibiotic class selectors:

 ``` r
+
 antibiogram(example_isolates,
  antibiotics = c(aminoglycosides(), carbapenems())
 )
@@ -631,7 +647,7 @@ antibiogram(example_isolates,
 ```

 | Pathogen | Amikacin | Gentamicin | Imipenem | Kanamycin | Meropenem | Tobramycin |
-|:-----------------|:---------------------|:--------------------|:---------------------|:----------------|:---------------------|:--------------------|
+|:---|:---|:---|:---|:---|:---|:---|
 | CoNS | 0% (0-8%,N=43) | 86% (82-90%,N=309) | 52% (37-67%,N=48) | 0% (0-8%,N=43) | 52% (37-67%,N=48) | 22% (12-35%,N=55) |
 | *E. coli* | 100% (98-100%,N=171) | 98% (96-99%,N=460) | 100% (99-100%,N=422) | NA | 100% (99-100%,N=418) | 97% (96-99%,N=462) |
 | *E. faecalis* | 0% (0-9%,N=39) | 0% (0-9%,N=39) | 100% (91-100%,N=38) | 0% (0-9%,N=39) | NA | 0% (0-9%,N=39) |
@@ -659,6 +675,7 @@ Ukrainian, Urdu, or Vietnamese. In this next example, we force the
 language to be Spanish using the `language` argument:

 ``` r
+
 antibiogram(example_isolates,
  mo_transform = "gramstain",
  antibiotics = aminoglycosides(),
@@ -670,7 +687,7 @@ antibiogram(example_isolates,
 ```

 | Patógeno | Amikacina | Gentamicina | Kanamicina | Tobramicina |
-|:--------------|:-------------------|:--------------------|:----------------|:-------------------|
+|:---|:---|:---|:---|:---|
 | Gram negativo | 98% (96-99%,N=256) | 96% (95-98%,N=684) | 0% (0-10%,N=35) | 96% (94-97%,N=686) |
 | Gram positivo | 0% (0-1%,N=436) | 63% (60-66%,N=1170) | 0% (0-1%,N=436) | 34% (31-38%,N=665) |

@@ -680,6 +697,7 @@ To create a combined antibiogram, use antibiotic codes or names with a
 plus `+` character like this:

 ``` r
+
 combined_ab <- antibiogram(example_isolates,
  antibiotics = c("TZP", "TZP+TOB", "TZP+GEN"),
  ab_transform = NULL
@@ -688,7 +706,7 @@ combined_ab
 ```

 | Pathogen | TZP | TZP + GEN | TZP + TOB |
-|:-----------------|:---------------------|:---------------------|:---------------------|
+|:---|:---|:---|:---|
 | CoNS | 30% (16-49%,N=33) | 97% (95-99%,N=274) | NA |
 | *E. coli* | 94% (92-96%,N=416) | 100% (98-100%,N=459) | 99% (97-100%,N=461) |
 | *K. pneumoniae* | 89% (77-96%,N=53) | 93% (83-98%,N=58) | 93% (83-98%,N=58) |
@@ -707,6 +725,7 @@ be used. This can be any column in the data, or e.g. an
 on certain columns:

 ``` r
+
 antibiogram(example_isolates,
  antibiotics = c(aminoglycosides(), carbapenems()),
  syndromic_group = "ward"
@@ -717,7 +736,7 @@ antibiogram(example_isolates,
 ```

 | Syndromic Group | Pathogen | Amikacin | Gentamicin | Imipenem | Kanamycin | Meropenem | Tobramycin |
-|:----------------|:-----------------|:---------------------|:--------------------|:---------------------|:----------------|:---------------------|:--------------------|
+|:---|:---|:---|:---|:---|:---|:---|:---|
 | Clinical | CoNS | NA | 89% (84-93%,N=205) | 57% (39-74%,N=35) | NA | 57% (39-74%,N=35) | 26% (12-45%,N=31) |
 | ICU | CoNS | NA | 79% (68-88%,N=73) | NA | NA | NA | NA |
 | Outpatient | CoNS | NA | 84% (66-95%,N=31) | NA | NA | NA | NA |
@@ -745,6 +764,7 @@ susceptibility estimates, weighted by pathogen incidence and
 antimicrobial susceptibility patterns.

 ``` r
+
 example_isolates %>%
  wisca(
    antibiotics = c("TZP", "TZP+TOB", "TZP+GEN"),
@@ -753,7 +773,7 @@ example_isolates %>%
 ```

 | Piperacillin/tazobactam | Piperacillin/tazobactam + Gentamicin | Piperacillin/tazobactam + Tobramycin |
-|:------------------------|:-------------------------------------|:-------------------------------------|
+|:---|:---|:---|
 | 69.4% (64.3-74.3%) | 92.6% (91.1-93.9%) | 88.7% (85.8-91.2%) |

 WISCA uses a **Bayesian decision model** to integrate data from multiple
@@ -775,6 +795,7 @@ grouped `tibble`, i.e., using
 first:

 ``` r
+
 example_isolates %>%
  top_n_microorganisms(n = 10) %>%
  group_by(
@@ -785,7 +806,7 @@ example_isolates %>%
 ```

 | age_group | gender | Piperacillin/tazobactam | Piperacillin/tazobactam + Gentamicin | Piperacillin/tazobactam + Tobramycin |
-|:----------|:-------|:------------------------|:-------------------------------------|:-------------------------------------|
+|:---|:---|:---|:---|:---|
 | 0-24 | F | 56.6% (25.2-83.9%) | 73.6% (48-91.6%) | 68.6% (42.9-89.5%) |
 | 0-24 | M | 60.3% (28.4-87.1%) | 79.7% (57.6-94.2%) | 60.1% (29.5-87.7%) |
 | 25-49 | F | 66.6% (45.6-85.5%) | 91.7% (84.6-96.7%) | 83% (67.9-94%) |
@@ -803,6 +824,7 @@ from the `ggplot2` packages, since this `AMR` package provides an
 extension to that function:

 ``` r
+
 autoplot(combined_ab)
 ```

@@ -847,6 +869,7 @@ equal to
 These functions can be used on their own:

 ``` r
+
 our_data_1st %>% resistance(AMX)
 #> ℹ `resistance()` assumes the EUCAST guideline and thus considers the 'I'
 #>   category susceptible. Set the `guideline` argument or the `AMR_guideline`
@@ -861,6 +884,7 @@ Or can be used in conjunction with
 both from the `dplyr` package:

 ``` r
+
 our_data_1st %>%
  group_by(hospital) %>%
  summarise(amoxicillin = resistance(AMX))
@@ -881,6 +905,7 @@ example with randomly generated MIC values for *Klebsiella pneumoniae*
 and ciprofloxacin:

 ``` r
+
 set.seed(123)
 mic_values <- random_mic(100)
 sir_values <- as.sir(mic_values, mo = "K. pneumoniae", ab = "cipro", guideline = "EUCAST 2024")
@@ -916,6 +941,7 @@ y-axis and
 colour-code SIR categories.

 ``` r
+
 # add a group
 my_data$group <- rep(c("A", "B", "C", "D"), each = 25)

@@ -946,6 +972,7 @@ has been extended by this package to directly plot MIC and disk
 diffusion values:

 ``` r
+
 autoplot(mic_values)
 ```

@@ -953,6 +980,7 @@ autoplot(mic_values)

 ``` r

+
 # by providing `mo` and `ab`, colours will indicate the SIR interpretation:
 autoplot(mic_values, mo = "K. pneumoniae", ab = "cipro", guideline = "EUCAST 2024")
 ```
--- a/articles/AMR_for_Python.html
+++ b/articles/AMR_for_Python.html
@@ -30,7 +30,7 @@

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/articles/AMR_for_Python.md
+++ b/articles/AMR_for_Python.md
@@ -169,7 +169,7 @@ AMR.microorganisms
 ```

 | mo | fullname | status | kingdom | gbif | gbif_parent | gbif_renamed_to | prevalence |
-|--------------|------------------------------------|----------|----------|----------|-------------|-----------------|------------|
+|----|----|----|----|----|----|----|----|
 | B_GRAMN | (unknown Gram-negatives) | unknown | Bacteria | None | None | None | 2.0 |
 | B_GRAMP | (unknown Gram-positives) | unknown | Bacteria | None | None | None | 2.0 |
 | B_ANAER-NEG | (unknown anaerobic Gram-negatives) | unknown | Bacteria | None | None | None | 2.0 |
@@ -187,7 +187,7 @@ AMR.antimicrobials
 ```

 | ab | cid | name | group | oral_ddd | oral_units | iv_ddd | iv_units |
-|-----|------------|-----------------------|--------------------------|----------|------------|--------|----------|
+|----|----|----|----|----|----|----|----|
 | AMA | 4649.0 | 4-aminosalicylic acid | Antimycobacterials | 12.00 | g | NaN | None |
 | ACM | 6450012.0 | Acetylmidecamycin | Macrolides/lincosamides | NaN | None | NaN | None |
 | ASP | 49787020.0 | Acetylspiramycin | Macrolides/lincosamides | NaN | None | NaN | None |
--- a/articles/AMR_with_tidymodels.html
+++ b/articles/AMR_with_tidymodels.html
@@ -30,7 +30,7 @@

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/articles/AMR_with_tidymodels.md
+++ b/articles/AMR_with_tidymodels.md
@@ -49,6 +49,7 @@ We begin by loading the required libraries and preparing the
 `example_isolates` dataset from the `AMR` package.

 ``` r
+
 # Load required libraries
 library(AMR) # For AMR data analysis
 library(tidymodels) # For machine learning workflows, and data manipulation (dplyr, tidyr, ...)
@@ -57,6 +58,7 @@ library(tidymodels) # For machine learning workflows, and data manipulation (dpl
 Prepare the data:

 ``` r
+
 # Your data could look like this:
 example_isolates
 #> # A tibble: 2,000 × 46
@@ -127,6 +129,7 @@ preprocessing, model specification, and fitting.
 We create a recipe to preprocess the data for modelling.

 ``` r
+
 # Define the recipe for data preprocessing
 resistance_recipe <- recipe(mo ~ ., data = data) %>%
  step_corr(c(aminoglycosides(), betalactams()), threshold = 0.9)
@@ -148,6 +151,7 @@ have with `step_corr()`, the necessary parameters can be estimated from
 a training set using `prep()`:

 ``` r
+
 prep(resistance_recipe)
 #> ℹ For `aminoglycosides()` using columns GEN (gentamicin), TOB (tobramycin), AMK
 #>   (amikacin), and KAN (kanamycin)
@@ -201,6 +205,7 @@ We define a logistic regression model since resistance prediction is a
 binary classification task.

 ``` r
+
 # Specify a logistic regression model
 logistic_model <- logistic_reg() %>%
  set_engine("glm") # Use the Generalised Linear Model engine
@@ -221,6 +226,7 @@ We bundle the recipe and model together into a `workflow`, which
 organises the entire modelling process.

 ``` r
+
 # Combine the recipe and model into a workflow
 resistance_workflow <- workflow() %>%
  add_recipe(resistance_recipe) %>% # Add the preprocessing recipe
@@ -248,6 +254,7 @@ Then, we fit the workflow on the training set and evaluate its
 performance.

 ``` r
+
 # Split data into training and testing sets
 set.seed(123) # For reproducibility
 data_split <- initial_split(data, prop = 0.8) # 80% training, 20% testing
@@ -271,6 +278,7 @@ they are stored in the recipe.
 Next, we evaluate the model on the testing data.

 ``` r
+
 # Make predictions on the testing set
 predictions <- fitted_workflow %>%
  predict(testing_data) # Generate predictions
@@ -338,6 +346,7 @@ AMR results of only aminoglycosides and beta-lactam antibiotics. The ROC
 curve looks like this:

 ``` r
+
 predictions %>%
  roc_curve(mo, `.pred_Gram-negative`) %>%
  autoplot()
@@ -390,6 +399,7 @@ Our goal is to:
 We use the `esbl_isolates` dataset that comes with the AMR package.

 ``` r
+
 # Load required libraries
 library(AMR)
 library(tidymodels)
@@ -437,6 +447,7 @@ selected using the new
 [`all_mic_predictors()`](https://amr-for-r.org/reference/amr-tidymodels.md):

 ``` r
+
 # Split into training and testing sets
 set.seed(123)
 split <- initial_split(data)
@@ -480,6 +491,7 @@ manual](https://parsnip.tidymodels.org/reference/details_boost_tree_xgboost.html
 could be much more precise.

 ``` r
+
 # Define the model
 model <- logistic_reg(mode = "classification") %>%
  set_engine("glm")
@@ -498,6 +510,7 @@ model
 #### 3. Building the Workflow

 ``` r
+
 # Create workflow
 workflow_model <- workflow() %>%
  add_recipe(mic_recipe) %>%
@@ -522,6 +535,7 @@ workflow_model
 ### **Training and Evaluating the Model**

 ``` r
+
 # Fit the model
 fitted <- fit(workflow_model, training_data)

@@ -566,6 +580,7 @@ We can visualise predictions by comparing predicted and actual ESBL
 status.

 ``` r
+
 library(ggplot2)

 ggplot(predictions, aes(x = esbl, fill = .pred_class)) +
@@ -583,6 +598,7 @@ ggplot(predictions, aes(x = esbl, fill = .pred_class)) +
 And plot the certainties too - how certain were the actual predictions?

 ``` r
+
 predictions %>%
  mutate(
    certainty = ifelse(.pred_class == "FALSE",
@@ -646,6 +662,7 @@ We start by transforming the `example_isolates` dataset into a
 structured time-series format.

 ``` r
+
 # Load required libraries
 library(AMR)
 library(tidymodels)
@@ -706,6 +723,7 @@ step, a model specification, and the fitting process.
 #### 1. Preprocessing with a Recipe

 ``` r
+
 # Define the recipe
 resistance_recipe_time <- recipe(res_AMX ~ year + gramstain, data = data_time) %>%
  step_dummy(gramstain, one_hot = TRUE) %>% # Convert categorical to numerical
@@ -739,6 +757,7 @@ resistance_recipe_time
 We use a linear regression model to predict resistance trends.

 ``` r
+
 # Define the linear regression model
 lm_model <- linear_reg() %>%
  set_engine("lm") # Use linear regression
@@ -759,6 +778,7 @@ lm_model
 We combine the preprocessing recipe and model into a workflow.

 ``` r
+
 # Create workflow
 resistance_workflow_time <- workflow() %>%
  add_recipe(resistance_recipe_time) %>%
@@ -788,6 +808,7 @@ We split the data into training and testing sets, fit the model, and
 evaluate performance.

 ``` r
+
 # Split the data
 set.seed(123)
 data_split_time <- initial_split(data_time, prop = 0.8)
@@ -829,6 +850,7 @@ metrics_time
 We plot resistance trends over time for amoxicillin.

 ``` r
+
 library(ggplot2)

 # Plot actual vs predicted resistance over time
@@ -849,6 +871,7 @@ Additionally, we can visualise resistance trends in `ggplot2` and
 directly add linear models there:

 ``` r
+
 ggplot(data_time, aes(x = year, y = res_AMX, color = gramstain)) +
  geom_line() +
  labs(
--- a/articles/EUCAST.html
+++ b/articles/EUCAST.html
@@ -30,7 +30,7 @@

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/articles/EUCAST.md
+++ b/articles/EUCAST.md
@@ -36,6 +36,7 @@ function resolves this, by applying the latest ‘EUCAST Expected
 Resistant Phenotypes’ guideline:

 ``` r
+
 oops <- tibble::tibble(
  mo = c(
    "Klebsiella pneumoniae",
@@ -64,6 +65,7 @@ that uses the same guideline, but allows to check for one or more
 specific microorganisms or antimicrobials:

 ``` r
+
 mo_is_intrinsic_resistant(
  c("Klebsiella pneumoniae", "Escherichia coli"),
  "ampicillin"
@@ -83,6 +85,7 @@ other antimicrobials drugs. This process is called *interpretive
 reading*, and is basically a form of imputation:

 ``` r
+
 data <- tibble::tibble(
  mo = c(
    "Staphylococcus aureus",
@@ -102,6 +105,7 @@ data <- tibble::tibble(
 ```

 ``` r
+
 data
 ```

@@ -114,6 +118,7 @@ data
 | Pseudomonas aeruginosa | \-  | \-  | \-  | \-  | \-  |  S  |  S  |

 ``` r
+
 eucast_rules(data, overwrite = TRUE)
 ```

--- a/articles/PCA.html
+++ b/articles/PCA.html
@@ -30,7 +30,7 @@

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/articles/PCA.md
+++ b/articles/PCA.md
@@ -11,6 +11,7 @@ For PCA, we need to transform our AMR data first. This is what the
 `example_isolates` data set in this package looks like:

 ``` r
+
 library(AMR)
 library(dplyr)
 glimpse(example_isolates)
@@ -68,6 +69,7 @@ Now to transform this to a data set with only resistance percentages per
 taxonomic order and genus:

 ``` r
+
 resistance_data <- example_isolates %>%
  group_by(
    order = mo_order(mo), # group on anything, like order
@@ -103,6 +105,7 @@ automatically filter on rows that contain numeric values in all selected
 variables, so we now only need to do:

 ``` r
+
 pca_result <- pca(resistance_data)
 #> ℹ Columns selected for PCA: "\033[1mAMC\033[22m", "\033[1mCAZ\033[22m",
 #>   "\033[1mCTX\033[22m", "\033[1mCXM\033[22m", "\033[1mGEN\033[22m",
@@ -114,6 +117,7 @@ The result can be reviewed with the good old
 [`summary()`](https://rdrr.io/r/base/summary.html) function:

 ``` r
+
 summary(pca_result)
 #> Groups (n=4, named as 'order'):
 #> [1] "Caryophanales"    "Enterobacterales" "Lactobacillales"  "Pseudomonadales"
@@ -137,6 +141,7 @@ microorganism.
 ## Plotting the results

 ``` r
+
 biplot(pca_result)
 ```

@@ -148,6 +153,7 @@ better with our new
 function, that automatically adds the right labels and even groups:

 ``` r
+
 ggplot_pca(pca_result)
 ```

@@ -156,6 +162,7 @@ ggplot_pca(pca_result)
 You can also print an ellipse per group, and edit the appearance:

 ``` r
+
 ggplot_pca(pca_result, ellipse = TRUE) +
  ggplot2::labs(title = "An AMR/PCA biplot!")
 ```
--- a/articles/WHONET.html
+++ b/articles/WHONET.html
@@ -30,7 +30,7 @@

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/articles/WHONET.md
+++ b/articles/WHONET.md
@@ -11,6 +11,7 @@ date fields are imported correctly.
 An example syntax could look like this:

 ``` r
+
 library(readxl)
 data <- read_excel(path = "path/to/your/file.xlsx")
 ```
@@ -27,6 +28,7 @@ I suggest you read about it on their website:
 <https://www.tidyverse.org/>.

 ``` r
+
 library(dplyr) # part of tidyverse
 library(ggplot2) # part of tidyverse
 library(AMR) # this package
@@ -50,6 +52,7 @@ analysis:
  for.

 ``` r
+
 # transform variables
 data <- WHONET %>%
  # get microbial ID based on given organism
@@ -68,6 +71,7 @@ function can be used to create frequency tables.
 So let’s check our data, with a couple of frequency tables:

 ``` r
+
 # our newly created `mo` variable, put in the mo_name() function
 data %>% freq(mo_name(mo), nmax = 10)
 ```
@@ -83,7 +87,7 @@ Shortest: 11
 Longest: 40

 |  | Item | Count | Percent | Cum. Count | Cum. Percent |
-|:----|:-----------------------------------------|------:|--------:|-----------:|-------------:|
+|:---|:---|---:|---:|---:|---:|
 | 1 | Escherichia coli | 245 | 49.0% | 245 | 49.0% |
 | 2 | Coagulase-negative Staphylococcus (CoNS) | 74 | 14.8% | 319 | 63.8% |
 | 3 | Staphylococcus epidermidis | 38 | 7.6% | 357 | 71.4% |
@@ -98,6 +102,7 @@ Longest: 40
 (omitted 28 entries, n = 57 \[11.4%\])

 ``` r
+
 # our transformed antibiotic columns
 # amoxicillin/clavulanic acid (J01CR02) as an example
 data %>% freq(AMC_ND2)
@@ -132,6 +137,7 @@ included [`ggplot_sir()`](https://amr-for-r.org/reference/ggplot_sir.md)
 function:

 ``` r
+
 data %>%
  group_by(Country) %>%
  select(Country, AMP_ND2, AMC_ED20, CAZ_ED10, CIP_ED5) %>%
--- a/articles/WISCA.html
+++ b/articles/WISCA.html
@@ -30,7 +30,7 @@

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -151,7 +151,7 @@ isolates. Therefore, traditional antibiograms:</p>
 regimen.</li>
 </ul>
 <p>We can write this as:</p>
-<p><math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mtext mathvariant="normal">Coverage</mtext><mo>=</mo><munder><mo>∑</mo><mi>i</mi></munder><mrow><mo stretchy="true" form="prefix">(</mo><msub><mtext mathvariant="normal">Incidence</mtext><mi>i</mi></msub><mo>×</mo><msub><mtext mathvariant="normal">Susceptibility</mtext><mi>i</mi></msub><mo stretchy="true" form="postfix">)</mo></mrow></mrow><annotation encoding="application/x-tex">\text{Coverage} = \sum_i (\text{Incidence}_i \times \text{Susceptibility}_i)</annotation></semantics></math></p>
+<p><math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mtext mathvariant="normal">Coverage</mtext><mo>=</mo><munder><mo>∑</mo><mi>i</mi></munder><mo stretchy="false" form="prefix">(</mo><msub><mtext mathvariant="normal">Incidence</mtext><mi>i</mi></msub><mo>×</mo><msub><mtext mathvariant="normal">Susceptibility</mtext><mi>i</mi></msub><mo stretchy="false" form="postfix">)</mo></mrow><annotation encoding="application/x-tex">\text{Coverage} = \sum_i (\text{Incidence}_i \times \text{Susceptibility}_i)</annotation></semantics></math></p>
 <p>For example, suppose:</p>
 <ul>
 <li>
@@ -162,7 +162,7 @@ are susceptible to a drug.</li>
 <em>Klebsiella</em> are susceptible.</li>
 </ul>
 <p>Then:</p>
-<p><math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mtext mathvariant="normal">Coverage</mtext><mo>=</mo><mrow><mo stretchy="true" form="prefix">(</mo><mn>0.6</mn><mo>×</mo><mn>0.9</mn><mo stretchy="true" form="postfix">)</mo></mrow><mo>+</mo><mrow><mo stretchy="true" form="prefix">(</mo><mn>0.4</mn><mo>×</mo><mn>0.7</mn><mo stretchy="true" form="postfix">)</mo></mrow><mo>=</mo><mn>0.82</mn></mrow><annotation encoding="application/x-tex">\text{Coverage} = (0.6 \times 0.9) + (0.4 \times 0.7) = 0.82</annotation></semantics></math></p>
+<p><math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mtext mathvariant="normal">Coverage</mtext><mo>=</mo><mo stretchy="false" form="prefix">(</mo><mn>0.6</mn><mo>×</mo><mn>0.9</mn><mo stretchy="false" form="postfix">)</mo><mo>+</mo><mo stretchy="false" form="prefix">(</mo><mn>0.4</mn><mo>×</mo><mn>0.7</mn><mo stretchy="false" form="postfix">)</mo><mo>=</mo><mn>0.82</mn></mrow><annotation encoding="application/x-tex">\text{Coverage} = (0.6 \times 0.9) + (0.4 \times 0.7) = 0.82</annotation></semantics></math></p>
 <p>But in real data, incidence and susceptibility are <strong>estimated
 from samples</strong>, so they carry uncertainty. WISCA models this
 <strong>probabilistically</strong>, using conjugate Bayesian
@@ -180,16 +180,16 @@ distributions.</p>
 <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mi>K</mi><annotation encoding="application/x-tex">K</annotation></semantics></math>
 be the number of pathogens,</li>
 <li>
-<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>α</mi><mo>=</mo><mrow><mo stretchy="true" form="prefix">(</mo><mn>1</mn><mo>,</mo><mn>1</mn><mo>,</mo><mi>…</mi><mo>,</mo><mn>1</mn><mo stretchy="true" form="postfix">)</mo></mrow></mrow><annotation encoding="application/x-tex">\alpha = (1, 1, \ldots, 1)</annotation></semantics></math>
+<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>α</mi><mo>=</mo><mo stretchy="false" form="prefix">(</mo><mn>1</mn><mo>,</mo><mn>1</mn><mo>,</mo><mi>…</mi><mo>,</mo><mn>1</mn><mo stretchy="false" form="postfix">)</mo></mrow><annotation encoding="application/x-tex">\alpha = (1, 1, \ldots, 1)</annotation></semantics></math>
 be a <strong>Dirichlet</strong> prior (uniform),</li>
 <li>
-<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>n</mi><mo>=</mo><mrow><mo stretchy="true" form="prefix">(</mo><msub><mi>n</mi><mn>1</mn></msub><mo>,</mo><mi>…</mi><mo>,</mo><msub><mi>n</mi><mi>K</mi></msub><mo stretchy="true" form="postfix">)</mo></mrow></mrow><annotation encoding="application/x-tex">n = (n_1, \ldots, n_K)</annotation></semantics></math>
+<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>n</mi><mo>=</mo><mo stretchy="false" form="prefix">(</mo><msub><mi>n</mi><mn>1</mn></msub><mo>,</mo><mi>…</mi><mo>,</mo><msub><mi>n</mi><mi>K</mi></msub><mo stretchy="false" form="postfix">)</mo></mrow><annotation encoding="application/x-tex">n = (n_1, \ldots, n_K)</annotation></semantics></math>
 be the observed counts per species.</li>
 </ul>
 <p>Then the posterior incidence is:</p>
-<p><math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>p</mi><mo>∼</mo><mtext mathvariant="normal">Dirichlet</mtext><mrow><mo stretchy="true" form="prefix">(</mo><msub><mi>α</mi><mn>1</mn></msub><mo>+</mo><msub><mi>n</mi><mn>1</mn></msub><mo>,</mo><mi>…</mi><mo>,</mo><msub><mi>α</mi><mi>K</mi></msub><mo>+</mo><msub><mi>n</mi><mi>K</mi></msub><mo stretchy="true" form="postfix">)</mo></mrow></mrow><annotation encoding="application/x-tex">p \sim \text{Dirichlet}(\alpha_1 + n_1, \ldots, \alpha_K + n_K)</annotation></semantics></math></p>
+<p><math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>p</mi><mo>∼</mo><mtext mathvariant="normal">Dirichlet</mtext><mo stretchy="false" form="prefix">(</mo><msub><mi>α</mi><mn>1</mn></msub><mo>+</mo><msub><mi>n</mi><mn>1</mn></msub><mo>,</mo><mi>…</mi><mo>,</mo><msub><mi>α</mi><mi>K</mi></msub><mo>+</mo><msub><mi>n</mi><mi>K</mi></msub><mo stretchy="false" form="postfix">)</mo></mrow><annotation encoding="application/x-tex">p \sim \text{Dirichlet}(\alpha_1 + n_1, \ldots, \alpha_K + n_K)</annotation></semantics></math></p>
 <p>To simulate from this, we use:</p>
-<p><math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><msub><mi>x</mi><mi>i</mi></msub><mo>∼</mo><mtext mathvariant="normal">Gamma</mtext><mrow><mo stretchy="true" form="prefix">(</mo><msub><mi>α</mi><mi>i</mi></msub><mo>+</mo><msub><mi>n</mi><mi>i</mi></msub><mo>,</mo><mspace width="0.222em"></mspace><mn>1</mn><mo stretchy="true" form="postfix">)</mo></mrow><mo>,</mo><mspace width="1.0em"></mspace><msub><mi>p</mi><mi>i</mi></msub><mo>=</mo><mfrac><msub><mi>x</mi><mi>i</mi></msub><mrow><munderover><mo>∑</mo><mrow><mi>j</mi><mo>=</mo><mn>1</mn></mrow><mi>K</mi></munderover><msub><mi>x</mi><mi>j</mi></msub></mrow></mfrac></mrow><annotation encoding="application/x-tex">x_i \sim \text{Gamma}(\alpha_i + n_i,\ 1), \quad p_i = \frac{x_i}{\sum_{j=1}^{K} x_j}</annotation></semantics></math></p>
+<p><math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><msub><mi>x</mi><mi>i</mi></msub><mo>∼</mo><mtext mathvariant="normal">Gamma</mtext><mo stretchy="false" form="prefix">(</mo><msub><mi>α</mi><mi>i</mi></msub><mo>+</mo><msub><mi>n</mi><mi>i</mi></msub><mo>,</mo><mspace width="0.222em"></mspace><mn>1</mn><mo stretchy="false" form="postfix">)</mo><mo>,</mo><mspace width="1.0em"></mspace><msub><mi>p</mi><mi>i</mi></msub><mo>=</mo><mfrac><msub><mi>x</mi><mi>i</mi></msub><mrow><munderover><mo>∑</mo><mrow><mi>j</mi><mo>=</mo><mn>1</mn></mrow><mi>K</mi></munderover><msub><mi>x</mi><mi>j</mi></msub></mrow></mfrac></mrow><annotation encoding="application/x-tex">x_i \sim \text{Gamma}(\alpha_i + n_i,\ 1), \quad p_i = \frac{x_i}{\sum_{j=1}^{K} x_j}</annotation></semantics></math></p>
 </div>
 <div class="section level3">
 <h3 id="susceptibility">Susceptibility<a class="anchor" aria-label="anchor" href="#susceptibility"></a>
@@ -197,7 +197,7 @@ be the observed counts per species.</li>
 <p>Each pathogen–regimen pair has a prior and data:</p>
 <ul>
 <li>Prior:
-<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mtext mathvariant="normal">Beta</mtext><mrow><mo stretchy="true" form="prefix">(</mo><msub><mi>α</mi><mn>0</mn></msub><mo>,</mo><msub><mi>β</mi><mn>0</mn></msub><mo stretchy="true" form="postfix">)</mo></mrow></mrow><annotation encoding="application/x-tex">\text{Beta}(\alpha_0, \beta_0)</annotation></semantics></math>,
+<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mtext mathvariant="normal">Beta</mtext><mo stretchy="false" form="prefix">(</mo><msub><mi>α</mi><mn>0</mn></msub><mo>,</mo><msub><mi>β</mi><mn>0</mn></msub><mo stretchy="false" form="postfix">)</mo></mrow><annotation encoding="application/x-tex">\text{Beta}(\alpha_0, \beta_0)</annotation></semantics></math>,
 with default
 <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><msub><mi>α</mi><mn>0</mn></msub><mo>=</mo><msub><mi>β</mi><mn>0</mn></msub><mo>=</mo><mn>1</mn></mrow><annotation encoding="application/x-tex">\alpha_0 = \beta_0 = 1</annotation></semantics></math>
 </li>
@@ -213,7 +213,7 @@ category could also include values SDD (susceptible, dose-dependent) and
 I (intermediate [CLSI], or susceptible, increased exposure
 [EUCAST]).</p>
 <p>Then the posterior is:</p>
-<p><math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>θ</mi><mo>∼</mo><mtext mathvariant="normal">Beta</mtext><mrow><mo stretchy="true" form="prefix">(</mo><msub><mi>α</mi><mn>0</mn></msub><mo>+</mo><mi>S</mi><mo>,</mo><mspace width="0.222em"></mspace><msub><mi>β</mi><mn>0</mn></msub><mo>+</mo><mi>N</mi><mo>−</mo><mi>S</mi><mo stretchy="true" form="postfix">)</mo></mrow></mrow><annotation encoding="application/x-tex">\theta \sim \text{Beta}(\alpha_0 + S,\ \beta_0 + N - S)</annotation></semantics></math></p>
+<p><math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>θ</mi><mo>∼</mo><mtext mathvariant="normal">Beta</mtext><mo stretchy="false" form="prefix">(</mo><msub><mi>α</mi><mn>0</mn></msub><mo>+</mo><mi>S</mi><mo>,</mo><mspace width="0.222em"></mspace><msub><mi>β</mi><mn>0</mn></msub><mo>+</mo><mi>N</mi><mo>−</mo><mi>S</mi><mo stretchy="false" form="postfix">)</mo></mrow><annotation encoding="application/x-tex">\theta \sim \text{Beta}(\alpha_0 + S,\ \beta_0 + N - S)</annotation></semantics></math></p>
 </div>
 <div class="section level3">
 <h3 id="final-coverage-estimate">Final coverage estimate<a class="anchor" aria-label="anchor" href="#final-coverage-estimate"></a>
@@ -224,7 +224,7 @@ I (intermediate [CLSI], or susceptible, increased exposure
 <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>𝐩</mi><mo>∼</mo><mtext mathvariant="normal">Dirichlet</mtext></mrow><annotation encoding="application/x-tex">\boldsymbol{p} \sim \text{Dirichlet}</annotation></semantics></math>
 </li>
 <li>Simulate susceptibility:
-<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><msub><mi>θ</mi><mi>i</mi></msub><mo>∼</mo><mtext mathvariant="normal">Beta</mtext><mrow><mo stretchy="true" form="prefix">(</mo><mn>1</mn><mo>+</mo><msub><mi>S</mi><mi>i</mi></msub><mo>,</mo><mspace width="0.222em"></mspace><mn>1</mn><mo>+</mo><msub><mi>R</mi><mi>i</mi></msub><mo stretchy="true" form="postfix">)</mo></mrow></mrow><annotation encoding="application/x-tex">\theta_i \sim \text{Beta}(1 + S_i,\ 1 + R_i)</annotation></semantics></math>
+<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><msub><mi>θ</mi><mi>i</mi></msub><mo>∼</mo><mtext mathvariant="normal">Beta</mtext><mo stretchy="false" form="prefix">(</mo><mn>1</mn><mo>+</mo><msub><mi>S</mi><mi>i</mi></msub><mo>,</mo><mspace width="0.222em"></mspace><mn>1</mn><mo>+</mo><msub><mi>R</mi><mi>i</mi></msub><mo stretchy="false" form="postfix">)</mo></mrow><annotation encoding="application/x-tex">\theta_i \sim \text{Beta}(1 + S_i,\ 1 + R_i)</annotation></semantics></math>
 </li>
 <li>Combine:</li>
 </ol>
--- a/articles/WISCA.md
+++ b/articles/WISCA.md
@@ -58,7 +58,9 @@ This means combining two things:

 We can write this as:

-$$\text{Coverage} = \sum\limits_{i}\left( \text{Incidence}_{i} \times \text{Susceptibility}_{i} \right)$$
+``` math
+\text{Coverage} = \sum_i (\text{Incidence}_i \times \text{Susceptibility}_i)
+```

 For example, suppose:

@@ -69,7 +71,9 @@ For example, suppose:

 Then:

-$$\text{Coverage} = (0.6 \times 0.9) + (0.4 \times 0.7) = 0.82$$
+``` math
+\text{Coverage} = (0.6 \times 0.9) + (0.4 \times 0.7) = 0.82
+```

 But in real data, incidence and susceptibility are **estimated from
 samples**, so they carry uncertainty. WISCA models this
@@ -81,45 +85,53 @@ samples**, so they carry uncertainty. WISCA models this

 Let:

- $K$ be the number of pathogens,
- $\alpha = (1,1,\ldots,1)$ be a **Dirichlet** prior (uniform),
- $n = \left( n_{1},\ldots,n_{K} \right)$ be the observed counts per
-  species.
+- $`K`$ be the number of pathogens,
+- $`\alpha = (1, 1, \ldots, 1)`$ be a **Dirichlet** prior (uniform),
+- $`n = (n_1, \ldots, n_K)`$ be the observed counts per species.

 Then the posterior incidence is:

-$$p \sim \text{Dirichlet}\left( \alpha_{1} + n_{1},\ldots,\alpha_{K} + n_{K} \right)$$
+``` math
+p \sim \text{Dirichlet}(\alpha_1 + n_1, \ldots, \alpha_K + n_K)
+```

 To simulate from this, we use:

-$$x_{i} \sim \text{Gamma}\left( \alpha_{i} + n_{i},\ 1 \right),\quad p_{i} = \frac{x_{i}}{\sum\limits_{j = 1}^{K}x_{j}}$$
+``` math
+x_i \sim \text{Gamma}(\alpha_i + n_i,\ 1), \quad p_i = \frac{x_i}{\sum_{j=1}^{K} x_j}
+```

 ### Susceptibility

 Each pathogen–regimen pair has a prior and data:

- Prior: $\text{Beta}\left( \alpha_{0},\beta_{0} \right)$, with default
-  $\alpha_{0} = \beta_{0} = 1$
- Data: $S$ susceptible out of $N$ tested
+- Prior: $`\text{Beta}(\alpha_0, \beta_0)`$, with default
+  $`\alpha_0 = \beta_0 = 1`$
+- Data: $`S`$ susceptible out of $`N`$ tested

-The $S$ category could also include values SDD (susceptible,
+The $`S`$ category could also include values SDD (susceptible,
 dose-dependent) and I (intermediate \[CLSI\], or susceptible, increased
 exposure \[EUCAST\]).

 Then the posterior is:

-$$\theta \sim \text{Beta}\left( \alpha_{0} + S,\ \beta_{0} + N - S \right)$$
+``` math
+\theta \sim \text{Beta}(\alpha_0 + S,\ \beta_0 + N - S)
+```

 ### Final coverage estimate

 Putting it together:

-1.  Simulate pathogen incidence: $\mathbf{p} \sim \text{Dirichlet}$
+1.  Simulate pathogen incidence:
+    $`\boldsymbol{p} \sim \text{Dirichlet}`$
 2.  Simulate susceptibility:
-    $\theta_{i} \sim \text{Beta}\left( 1 + S_{i},\ 1 + R_{i} \right)$
+    $`\theta_i \sim \text{Beta}(1 + S_i,\ 1 + R_i)`$
 3.  Combine:

-$$\text{Coverage} = \sum\limits_{i = 1}^{K}p_{i} \cdot \theta_{i}$$
+``` math
+\text{Coverage} = \sum_{i=1}^{K} p_i \cdot \theta_i
+```

 Repeat this simulation (e.g. 1000×) and summarise:

@@ -131,6 +143,7 @@ Repeat this simulation (e.g. 1000×) and summarise:
 ### Prepare data and simulate synthetic syndrome

 ``` r
+
 library(AMR)
 data <- example_isolates

@@ -164,6 +177,7 @@ data$syndrome <- ifelse(data$mo %like% "coli", "UTI", "No UTI")
 ### Basic WISCA antibiogram

 ``` r
+
 wisca(data,
  antimicrobials = c("AMC", "CIP", "GEN")
 )
@@ -176,18 +190,20 @@ wisca(data,
 ### Use combination regimens

 ``` r
+
 wisca(data,
  antimicrobials = c("AMC", "AMC + CIP", "AMC + GEN")
 )
 ```

 | Amoxicillin/clavulanic acid | Amoxicillin/clavulanic acid + Ciprofloxacin | Amoxicillin/clavulanic acid + Gentamicin |
-|:----------------------------|:--------------------------------------------|:-----------------------------------------|
+|:---|:---|:---|
 | 73.8% (71.8-75.7%) | 87.5% (85.9-89%) | 89.7% (88.2-91.1%) |

 ### Stratify by syndrome

 ``` r
+
 wisca(data,
  antimicrobials = c("AMC", "AMC + CIP", "AMC + GEN"),
  syndromic_group = "syndrome"
@@ -195,7 +211,7 @@ wisca(data,
 ```

 | Syndromic Group | Amoxicillin/clavulanic acid | Amoxicillin/clavulanic acid + Ciprofloxacin | Amoxicillin/clavulanic acid + Gentamicin |
-|:----------------|:----------------------------|:--------------------------------------------|:-----------------------------------------|
+|:---|:---|:---|:---|
 | No UTI | 70.1% (67.8-72.3%) | 85.2% (83.1-87.2%) | 87.1% (85.3-88.7%) |
 | UTI | 80.9% (77.7-83.8%) | 88.2% (85.7-90.5%) | 90.9% (88.7-93%) |

@@ -204,6 +220,7 @@ for the [`wisca()`](https://amr-for-r.org/reference/antibiogram.md)
 function too:

 ``` r
+
 wisca(data,
  antimicrobials = c("AMC", "AMC + CIP", "AMC + GEN"),
  syndromic_group = gsub("UTI", "UCI", data$syndrome),
@@ -212,7 +229,7 @@ wisca(data,
 ```

 | Grupo sindrómico | Amoxicilina/ácido clavulánico | Amoxicilina/ácido clavulánico + Ciprofloxacina | Amoxicilina/ácido clavulánico + Gentamicina |
-|:-----------------|:------------------------------|:-----------------------------------------------|:--------------------------------------------|
+|:---|:---|:---|:---|
 | No UCI | 70% (67.8-72.4%) | 85.3% (83.3-87.2%) | 87% (85.3-88.8%) |
 | UCI | 80.9% (77.7-83.9%) | 88.2% (85.5-90.6%) | 90.9% (88.7-93%) |

@@ -242,6 +259,7 @@ WISCA enables:
 It is available in the `AMR` package via either:

 ``` r
+
 wisca(...)

 antibiogram(..., wisca = TRUE)
--- a/articles/datasets.html
+++ b/articles/datasets.html
@@ -30,7 +30,7 @@

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -80,7 +80,7 @@
  <main id="main" class="col-md-9"><div class="page-header">
      <img src="../logo.svg" class="logo" alt=""><h1>Download data sets for download / own use</h1>
            
-            <h4 data-toc-skip class="date">25 April 2026</h4>
+            <h4 data-toc-skip class="date">30 April 2026</h4>
      
      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/vignettes/datasets.Rmd" class="external-link"><code>vignettes/datasets.Rmd</code></a></small>
      <div class="d-none name"><code>datasets.Rmd</code></div>
--- a/articles/datasets.md
+++ b/articles/datasets.md
@@ -79,7 +79,7 @@ Included (sub)species per taxonomic kingdom:
 First 6 rows when filtering on genus *Escherichia*:

 | mo | fullname | status | kingdom | phylum | class | order | family | genus | species | subspecies | rank | ref | oxygen_tolerance | source | lpsn | lpsn_parent | lpsn_renamed_to | mycobank | mycobank_parent | mycobank_renamed_to | gbif | gbif_parent | gbif_renamed_to | prevalence | snomed |
-|:-----------------:|:--------------------------:|:--------:|:--------:|:--------------:|:-------------------:|:----------------:|:------------------:|:-----------:|:--------------:|:----------:|:----------:|:-----------------------:|:---------------------------:|:------:|:------:|:-----------:|:---------------:|:--------:|:---------------:|:-------------------:|:--------:|:-----------:|:---------------:|:----------:|:-----------------------------------------:|
+|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|
 | B_ESCHR | Escherichia | accepted | Bacteria | Pseudomonadota | Gammaproteobacteria | Enterobacterales | Enterobacteriaceae | Escherichia |  |  | genus | Castellani et al., 1919 | facultative anaerobe | LPSN | 515602 | 482 |  |  |  |  |  | 11158430 |  | 1 | 407310004, 407251000, 407281008, … |
 | B_ESCHR_ADCR | Escherichia adecarboxylata | synonym | Bacteria | Pseudomonadota | Gammaproteobacteria | Enterobacterales | Enterobacteriaceae | Escherichia | adecarboxylata |  | species | Leclerc, 1962 | likely facultative anaerobe | LPSN | 776052 | 515602 | 777447 |  |  |  |  |  |  | 1 |  |
 | B_ESCHR_ALBR | Escherichia albertii | accepted | Bacteria | Pseudomonadota | Gammaproteobacteria | Enterobacterales | Enterobacteriaceae | Escherichia | albertii |  | species | Huys et al., 2003 | facultative anaerobe | LPSN | 776053 | 515602 |  |  |  |  | 5427575 |  |  | 1 | 419388003 |
@@ -135,7 +135,7 @@ as comma separated values.
 **Example content**

 | ab | cid | name | group | atc | atc_group1 | atc_group2 | abbreviations | synonyms | oral_ddd | oral_units | iv_ddd | iv_units | loinc |
-|:---:|:--------:|:---------------------------:|:----------------------------------------------:|:------------------------------:|:-------------------------------------------:|:------------------------------------------------------------:|:-------------------:|:-------------------------------------------------------:|:--------:|:----------:|:------:|:--------:|:------------------------------:|
+|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|
 | AMK | 37768 | Amikacin | Aminoglycosides | D06AX12, J01GB06, QD06AX12, … | Aminoglycoside antibacterials | Other aminoglycosides | ak, ami, amik, … | amikacillin, amikacina, amikacine, … |  |  | 1.0 | g | 101493-5, 11-7, 12-5, … |
 | AMX | 33613 | Amoxicillin | Aminopenicillins, Penicillins, Beta-lactams | J01CA04, QG51AA03, QJ01CA04 | Beta-lactam antibacterials, penicillins | Penicillins with extended spectrum | ac, amox, amoxic, … | acuotricina, alfamox, alfida, … | 1.5 | g | 3.0 | g | 101498-4, 15-8, 16-6, … |
 | AMC | 23665637 | Amoxicillin/clavulanic acid | Aminopenicillins, Penicillins, Beta-lactams, … | J01CR02, QJ01CR02 | Beta-lactam antibacterials, penicillins | Combinations of penicillins, incl. beta-lactamase inhibitors | a/c, amcl, aml, … | amocla, amoclan, amoclav, … | 1.5 | g | 3.0 | g |  |
@@ -187,7 +187,7 @@ here](https://amr-for-r.org/reference/clinical_breakpoints.html).
 **Example content**

 | guideline | type | host | method | site | mo | mo_name | rank_index | ab | ab_name | ref_tbl | disk_dose | breakpoint_S | breakpoint_R | uti | is_SDD |
-|:-----------:|:-----:|:-----:|:------:|:----:|:-------------:|:--------------------------:|:----------:|:---:|:-----------------------------:|:---------------:|:--------------:|:------------:|:------------:|:-----:|:------:|
+|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|
 | EUCAST 2026 | human | human | DISK |  | B_ACHRMB_XYLS | Achromobacter xylosoxidans | 2 | MEM | Meropenem | A. xylosoxidans | 10 mcg | 26.000 | 20.000 | FALSE | FALSE |
 | EUCAST 2026 | human | human | MIC |  | B_ACHRMB_XYLS | Achromobacter xylosoxidans | 2 | MEM | Meropenem | A. xylosoxidans |  | 1.000 | 4.000 | FALSE | FALSE |
 | EUCAST 2026 | human | human | DISK |  | B_ACHRMB_XYLS | Achromobacter xylosoxidans | 2 | SXT | Trimethoprim/sulfamethoxazole | A. xylosoxidans | 1.25/23.75 mcg | 26.000 | 26.000 | FALSE | FALSE |
@@ -237,7 +237,7 @@ here](https://amr-for-r.org/reference/microorganisms.groups.html).
 **Example content**

 | mo_group | mo | mo_group_name | mo_name |
-|:--------------:|:------------:|:-------------------------------:|:---------------------------:|
+|:--:|:--:|:--:|:--:|
 | B_ACNTB_BMNN-C | B_ACNTB_BMNN | Acinetobacter baumannii complex | Acinetobacter baumannii |
 | B_ACNTB_BMNN-C | B_ACNTB_CLCC | Acinetobacter baumannii complex | Acinetobacter calcoaceticus |
 | B_ACNTB_BMNN-C | B_ACNTB_LCTC | Acinetobacter baumannii complex | Acinetobacter dijkshoorniae |
@@ -395,7 +395,7 @@ here](https://amr-for-r.org/reference/dosage.html).
 **Example content**

 | ab | name | type | dose | dose_times | administration | notes | original_txt | eucast_version |
-|:---:|:-----------:|:-----------------:|:-----------:|:----------:|:--------------:|:-----:|:------------------:|:--------------:|
+|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|
 | AMK | Amikacin | standard_dosage | 25-30 mg/kg | 1 | iv |  | 25-30 mg/kg x 1 iv | 15 |
 | AMX | Amoxicillin | high_dosage | 2 g | 6 | iv |  | 2 g x 6 iv | 15 |
 | AMX | Amoxicillin | standard_dosage | 1 g | 3 | iv |  | 1 g x 3-4 iv | 15 |
@@ -425,7 +425,7 @@ here](https://amr-for-r.org/reference/example_isolates.html).
 **Example content**

 | date | patient | age | gender | ward | mo | PEN | OXA | FLC | AMX | AMC | AMP | TZP | CZO | FEP | CXM | FOX | CTX | CAZ | CRO | GEN | TOB | AMK | KAN | TMP | SXT | NIT | FOS | LNZ | CIP | MFX | VAN | TEC | TCY | TGC | DOX | ERY | CLI | AZM | IPM | MEM | MTR | CHL | COL | MUP | RIF |
-|:----------:|:-------:|:---:|:------:|:--------:|:------------:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|
+|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|
 | 2002-01-02 | A77334 | 65 | F | Clinical | B_ESCHR_COLI | R |  |  |  | I |  |  |  |  | I |  |  |  |  |  |  |  |  | R | R |  |  | R |  |  | R | R | R |  |  | R | R | R |  |  |  |  |  |  | R |
 | 2002-01-03 | A77334 | 65 | F | Clinical | B_ESCHR_COLI | R |  |  |  | I |  |  |  |  | I |  |  |  |  |  |  |  |  | R | R |  |  | R |  |  | R | R | R |  |  | R | R | R |  |  |  |  |  |  | R |
 | 2002-01-07 | 067927 | 45 | F | ICU | B_STPHY_EPDR | R |  | R |  |  |  |  |  |  | R |  |  | R |  |  |  |  |  | S | S |  |  |  |  |  | S |  | S | S | S | R |  | R |  |  |  |  | R |  |  |
@@ -556,7 +556,7 @@ contain the trade names and LOINC codes as comma separated values.
 **Example content**

 | av | name | atc | cid | atc_group | synonyms | oral_ddd | oral_units | iv_ddd | iv_units | loinc |
-|:---:|:------------------:|:-------:|:---------:|:------------------------------------------------------------------:|:-----------------------------------------------------:|:--------:|:----------:|:------:|:--------:|:----------------------------:|
+|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|:--:|
 | ABA | Abacavir | J05AF06 | 441300 | Nucleoside and nucleotide reverse transcriptase inhibitors | abacavir sulfate, avacavir, ziagen | 0.6 | g |  |  | 29113-8, 30273-7, 30287-7, … |
 | ACI | Aciclovir | J05AB01 | 135398513 | Nucleosides and nucleotides excl. reverse transcriptase inhibitors | acicloftal, aciclovier, aciclovirum, … | 4.0 | g | 4 | g |  |
 | ADD | Adefovir dipivoxil | J05AF08 | 60871 | Nucleoside and nucleotide reverse transcriptase inhibitors | adefovir di, adefovir di ester, adefovir dipivoxyl, … | 10.0 | mg |  |  |  |
--- a/articles/index.html
+++ b/articles/index.html
@@ -7,7 +7,7 @@

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/authors.html
+++ b/authors.html
@@ -7,7 +7,7 @@

    <a class="navbar-brand me-2" href="index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/index.html
+++ b/index.html
@@ -33,7 +33,7 @@

    <a class="navbar-brand me-2" href="index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -145,24 +145,26 @@
 <span><span class="co">#&gt; ℹ Using column mo as input for `mo_fullname()`</span></span>
 <span><span class="co">#&gt; ℹ Using column mo as input for `mo_is_gram_negative()`</span></span>
 <span><span class="co">#&gt; ℹ Using column mo as input for `mo_is_intrinsic_resistant()`</span></span>
-<span><span class="co">#&gt; ℹ Determining intrinsic resistance based on 'EUCAST Expected Resistant</span></span>
-<span><span class="co">#&gt;   Phenotypes' v1.2 (2023). This note will be shown once per session.</span></span>
-<span><span class="co">#&gt; ℹ For `aminoglycosides()` using columns GEN (gentamicin), TOB (tobramycin), AMK</span></span>
-<span><span class="co">#&gt;   (amikacin), and KAN (kanamycin)</span></span>
-<span><span class="co">#&gt; ℹ For `carbapenems()` using columns IPM (imipenem) and MEM (meropenem)</span></span>
+<span><span class="co">#&gt; ℹ Determining intrinsic resistance based on 'EUCAST Expected</span></span>
+<span><span class="co">#&gt;   Resistant Phenotypes' v1.2 (2023). This note will be shown</span></span>
+<span><span class="co">#&gt;   once per session.</span></span>
+<span><span class="co">#&gt; ℹ For `aminoglycosides()` using columns GEN (gentamicin), TOB</span></span>
+<span><span class="co">#&gt;   (tobramycin), AMK (amikacin), and KAN (kanamycin)</span></span>
+<span><span class="co">#&gt; ℹ For `carbapenems()` using columns IPM (imipenem) and MEM</span></span>
+<span><span class="co">#&gt;   (meropenem)</span></span>
 <span><span class="co">#&gt; # A tibble: 35 × 7</span></span>
 <span><span class="co">#&gt;    bacteria         GEN   TOB   AMK   KAN   IPM   MEM  </span></span>
 <span><span class="co">#&gt;    &lt;chr&gt;            &lt;sir&gt; &lt;sir&gt; &lt;sir&gt; &lt;sir&gt; &lt;sir&gt; &lt;sir&gt;</span></span>
-<span><span class="co">#&gt;  1 Pseudomonas aeruginosa       I     S     NA    R     S     NA   </span></span>
-<span><span class="co">#&gt;  2 Pseudomonas aeruginosa       I     S     NA    R     S     NA   </span></span>
-<span><span class="co">#&gt;  3 Pseudomonas aeruginosa       I     S     NA    R     S     NA   </span></span>
-<span><span class="co">#&gt;  4 Pseudomonas aeruginosa       S     S     S     R     NA    S    </span></span>
-<span><span class="co">#&gt;  5 Pseudomonas aeruginosa       S     S     S     R     S     S    </span></span>
-<span><span class="co">#&gt;  6 Pseudomonas aeruginosa       S     S     S     R     S     S    </span></span>
-<span><span class="co">#&gt;  7 Stenotrophomonas maltophilia R     R     R     R     R     R    </span></span>
-<span><span class="co">#&gt;  8 Pseudomonas aeruginosa       S     S     S     R     NA    S    </span></span>
-<span><span class="co">#&gt;  9 Pseudomonas aeruginosa       S     S     S     R     NA    S    </span></span>
-<span><span class="co">#&gt; 10 Pseudomonas aeruginosa       S     S     S     R     S     S    </span></span>
+<span><span class="co">#&gt;  1 Pseudomonas aer… I     S     NA    R     S     NA   </span></span>
+<span><span class="co">#&gt;  2 Pseudomonas aer… I     S     NA    R     S     NA   </span></span>
+<span><span class="co">#&gt;  3 Pseudomonas aer… I     S     NA    R     S     NA   </span></span>
+<span><span class="co">#&gt;  4 Pseudomonas aer… S     S     S     R     NA    S    </span></span>
+<span><span class="co">#&gt;  5 Pseudomonas aer… S     S     S     R     S     S    </span></span>
+<span><span class="co">#&gt;  6 Pseudomonas aer… S     S     S     R     S     S    </span></span>
+<span><span class="co">#&gt;  7 Stenotrophomona… R     R     R     R     R     R    </span></span>
+<span><span class="co">#&gt;  8 Pseudomonas aer… S     S     S     R     NA    S    </span></span>
+<span><span class="co">#&gt;  9 Pseudomonas aer… S     S     S     R     NA    S    </span></span>
+<span><span class="co">#&gt; 10 Pseudomonas aer… S     S     S     R     S     S    </span></span>
 <span><span class="co">#&gt; # ℹ 25 more rows</span></span></code></pre></div>
 <p>With only having defined a row filter on Gram-negative bacteria with intrinsic resistance to cefotaxime (<code><a href="reference/mo_property.html">mo_is_gram_negative()</a></code> and <code><a href="reference/mo_property.html">mo_is_intrinsic_resistant()</a></code>) and a column selection on two antibiotic groups (<code><a href="reference/antimicrobial_selectors.html">aminoglycosides()</a></code> and <code><a href="reference/antimicrobial_selectors.html">carbapenems()</a></code>), the reference data about <a href="./reference/microorganisms.html">all microorganisms</a> and <a href="./reference/antimicrobials.html">all antimicrobials</a> in the <code>AMR</code> package make sure you get what you meant.</p>
 </div>
@@ -174,20 +176,21 @@
 <div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="fu"><a href="reference/antibiogram.html">antibiogram</a></span><span class="op">(</span><span class="va">example_isolates</span>,</span>
 <span>            antimicrobials <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fu"><a href="reference/antimicrobial_selectors.html">aminoglycosides</a></span><span class="op">(</span><span class="op">)</span>, <span class="fu"><a href="reference/antimicrobial_selectors.html">carbapenems</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="op">)</span></span>
-<span><span class="co">#&gt; ℹ For `aminoglycosides()` using columns GEN (gentamicin), TOB (tobramycin), AMK</span></span>
-<span><span class="co">#&gt;   (amikacin), and KAN (kanamycin)</span></span>
-<span><span class="co">#&gt; ℹ For `carbapenems()` using columns IPM (imipenem) and MEM (meropenem)</span></span></code></pre></div>
-<table style="width:100%;" class="table">
+<span><span class="co">#&gt; ℹ For `aminoglycosides()` using columns GEN (gentamicin), TOB</span></span>
+<span><span class="co">#&gt;   (tobramycin), AMK (amikacin), and KAN (kanamycin)</span></span>
+<span><span class="co">#&gt; ℹ For `carbapenems()` using columns IPM (imipenem) and MEM</span></span>
+<span><span class="co">#&gt;   (meropenem)</span></span></code></pre></div>
+<table class="table">
 <colgroup>
+<col width="12%">
+<col width="15%">
 <col width="14%">
-<col width="14%">
-<col width="14%">
-<col width="14%">
-<col width="14%">
-<col width="14%">
+<col width="15%">
+<col width="11%">
+<col width="15%">
 <col width="14%">
 </colgroup>
-<thead><tr class="header">
+<thead><tr>
 <th align="left">Pathogen</th>
 <th align="left">Amikacin</th>
 <th align="left">Gentamicin</th>
@@ -197,7 +200,7 @@
 <th align="left">Tobramycin</th>
 </tr></thead>
 <tbody>
-<tr class="odd">
+<tr>
 <td align="left">CoNS</td>
 <td align="left">0% (0-8%,N=43)</td>
 <td align="left">86% (82-90%,N=309)</td>
@@ -206,7 +209,7 @@
 <td align="left">52% (37-67%,N=48)</td>
 <td align="left">22% (12-35%,N=55)</td>
 </tr>
-<tr class="even">
+<tr>
 <td align="left"><em>E. coli</em></td>
 <td align="left">100% (98-100%,N=171)</td>
 <td align="left">98% (96-99%,N=460)</td>
@@ -215,7 +218,7 @@
 <td align="left">100% (99-100%,N=418)</td>
 <td align="left">97% (96-99%,N=462)</td>
 </tr>
-<tr class="odd">
+<tr>
 <td align="left"><em>E. faecalis</em></td>
 <td align="left">0% (0-9%,N=39)</td>
 <td align="left">0% (0-9%,N=39)</td>
@@ -224,7 +227,7 @@
 <td align="left">NA</td>
 <td align="left">0% (0-9%,N=39)</td>
 </tr>
-<tr class="even">
+<tr>
 <td align="left"><em>K. pneumoniae</em></td>
 <td align="left">NA</td>
 <td align="left">90% (79-96%,N=58)</td>
@@ -233,7 +236,7 @@
 <td align="left">100% (93-100%,N=53)</td>
 <td align="left">90% (79-96%,N=58)</td>
 </tr>
-<tr class="odd">
+<tr>
 <td align="left"><em>P. aeruginosa</em></td>
 <td align="left">NA</td>
 <td align="left">100% (88-100%,N=30)</td>
@@ -242,7 +245,7 @@
 <td align="left">NA</td>
 <td align="left">100% (88-100%,N=30)</td>
 </tr>
-<tr class="even">
+<tr>
 <td align="left"><em>P. mirabilis</em></td>
 <td align="left">NA</td>
 <td align="left">94% (80-99%,N=34)</td>
@@ -251,7 +254,7 @@
 <td align="left">NA</td>
 <td align="left">94% (80-99%,N=34)</td>
 </tr>
-<tr class="odd">
+<tr>
 <td align="left"><em>S. aureus</em></td>
 <td align="left">NA</td>
 <td align="left">99% (97-100%,N=233)</td>
@@ -260,7 +263,7 @@
 <td align="left">NA</td>
 <td align="left">98% (92-100%,N=86)</td>
 </tr>
-<tr class="even">
+<tr>
 <td align="left"><em>S. epidermidis</em></td>
 <td align="left">0% (0-8%,N=44)</td>
 <td align="left">79% (71-85%,N=163)</td>
@@ -269,7 +272,7 @@
 <td align="left">NA</td>
 <td align="left">51% (40-61%,N=89)</td>
 </tr>
-<tr class="odd">
+<tr>
 <td align="left"><em>S. hominis</em></td>
 <td align="left">NA</td>
 <td align="left">92% (84-97%,N=80)</td>
@@ -278,7 +281,7 @@
 <td align="left">NA</td>
 <td align="left">85% (74-93%,N=62)</td>
 </tr>
-<tr class="even">
+<tr>
 <td align="left"><em>S. pneumoniae</em></td>
 <td align="left">0% (0-3%,N=117)</td>
 <td align="left">0% (0-3%,N=117)</td>
@@ -296,25 +299,25 @@
 <span>            mo_transform <span class="op">=</span> <span class="st">"gramstain"</span><span class="op">)</span></span></code></pre></div>
 <table class="table">
 <colgroup>
-<col width="25%">
-<col width="25%">
-<col width="25%">
-<col width="25%">
+<col width="12%">
+<col width="21%">
+<col width="32%">
+<col width="32%">
 </colgroup>
-<thead><tr class="header">
+<thead><tr>
 <th align="left">Pathogen</th>
 <th align="left">Piperacillin/tazobactam</th>
 <th align="left">Piperacillin/tazobactam + Gentamicin</th>
 <th align="left">Piperacillin/tazobactam + Tobramycin</th>
 </tr></thead>
 <tbody>
-<tr class="odd">
+<tr>
 <td align="left">Gram-negative</td>
 <td align="left">88% (85-91%,N=641)</td>
 <td align="left">99% (97-99%,N=691)</td>
 <td align="left">98% (97-99%,N=693)</td>
 </tr>
-<tr class="even">
+<tr>
 <td align="left">Gram-positive</td>
 <td align="left">86% (82-89%,N=345)</td>
 <td align="left">98% (96-98%,N=1044)</td>
@@ -336,20 +339,20 @@
 <col width="26%">
 <col width="26%">
 </colgroup>
-<thead><tr class="header">
+<thead><tr>
 <th align="left">Збудник</th>
 <th align="left">Гентаміцин</th>
 <th align="left">Тобраміцин</th>
 <th align="left">Ципрофлоксацин</th>
 </tr></thead>
 <tbody>
-<tr class="odd">
+<tr>
 <td align="left">Грамнегативні</td>
 <td align="left">96% (95-98%,N=684)</td>
 <td align="left">96% (94-97%,N=686)</td>
 <td align="left">91% (88-93%,N=684)</td>
 </tr>
-<tr class="even">
+<tr>
 <td align="left">Грампозитивні</td>
 <td align="left">63% (60-66%,N=1170)</td>
 <td align="left">34% (31-38%,N=665)</td>
@@ -404,16 +407,18 @@
 <span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">summarise</a></span><span class="op">(</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/across.html" class="external-link">across</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="va">GEN</span>, <span class="va">TOB</span><span class="op">)</span>,</span>
 <span>                   <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span>total_R <span class="op">=</span> <span class="va">resistance</span>,</span>
 <span>                        conf_int <span class="op">=</span> <span class="kw">function</span><span class="op">(</span><span class="va">x</span><span class="op">)</span> <span class="fu"><a href="reference/proportion.html">sir_confidence_interval</a></span><span class="op">(</span><span class="va">x</span>, collapse <span class="op">=</span> <span class="st">"-"</span><span class="op">)</span><span class="op">)</span><span class="op">)</span><span class="op">)</span></span>
-<span><span class="co">#&gt; ℹ `resistance()` assumes the EUCAST guideline and thus considers the 'I'</span></span>
-<span><span class="co">#&gt;   category susceptible. Set the `guideline` argument or the `AMR_guideline`</span></span>
-<span><span class="co">#&gt;   option to either "CLSI" or "EUCAST", see `?AMR-options`.</span></span>
+<span><span class="co">#&gt; ℹ `resistance()` assumes the EUCAST guideline and thus</span></span>
+<span><span class="co">#&gt;   considers the 'I' category susceptible. Set the `guideline`</span></span>
+<span><span class="co">#&gt;   argument or the `AMR_guideline` option to either "CLSI" or</span></span>
+<span><span class="co">#&gt;   "EUCAST", see `?AMR-options`.</span></span>
 <span><span class="co">#&gt; ℹ This message will be shown once per session.</span></span>
 <span><span class="co">#&gt; # A tibble: 3 × 5</span></span>
-<span><span class="co">#&gt;   ward       GEN_total_R GEN_conf_int TOB_total_R TOB_conf_int</span></span>
-<span><span class="co">#&gt;   &lt;chr&gt;            &lt;dbl&gt; &lt;chr&gt;              &lt;dbl&gt; &lt;chr&gt;       </span></span>
-<span><span class="co">#&gt; 1 Clinical         0.229 0.205-0.254        0.315 0.284-0.347 </span></span>
-<span><span class="co">#&gt; 2 ICU              0.290 0.253-0.33         0.400 0.353-0.449 </span></span>
-<span><span class="co">#&gt; 3 Outpatient       0.2   0.131-0.285        0.368 0.254-0.493</span></span></code></pre></div>
+<span><span class="co">#&gt;   ward       GEN_total_R GEN_conf_int TOB_total_R</span></span>
+<span><span class="co">#&gt;   &lt;chr&gt;            &lt;dbl&gt; &lt;chr&gt;              &lt;dbl&gt;</span></span>
+<span><span class="co">#&gt; 1 Clinical         0.229 0.205-0.254        0.315</span></span>
+<span><span class="co">#&gt; 2 ICU              0.290 0.253-0.33         0.400</span></span>
+<span><span class="co">#&gt; 3 Outpatient       0.2   0.131-0.285        0.368</span></span>
+<span><span class="co">#&gt; # ℹ 1 more variable: TOB_conf_int &lt;chr&gt;</span></span></code></pre></div>
 <p>Or use <a href="https://amr-for-r.org/reference/antimicrobial_selectors.html">antimicrobial selectors</a> to select a series of antibiotic columns:</p>
 <div class="sourceCode" id="cb7"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://amr-for-r.org">AMR</a></span><span class="op">)</span></span>
@@ -425,15 +430,16 @@
 <span>  <span class="co"># calculate AMR using resistance(), over all aminoglycosides and polymyxins:</span></span>
 <span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">summarise</a></span><span class="op">(</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/across.html" class="external-link">across</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fu"><a href="reference/antimicrobial_selectors.html">aminoglycosides</a></span><span class="op">(</span><span class="op">)</span>, <span class="fu"><a href="reference/antimicrobial_selectors.html">polymyxins</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span>,</span>
 <span>            <span class="va">resistance</span><span class="op">)</span><span class="op">)</span></span>
-<span><span class="co">#&gt; ℹ For `aminoglycosides()` using columns GEN (gentamicin), TOB (tobramycin), AMK</span></span>
-<span><span class="co">#&gt;   (amikacin), and KAN (kanamycin)</span></span>
+<span><span class="co">#&gt; ℹ For `aminoglycosides()` using columns GEN (gentamicin), TOB</span></span>
+<span><span class="co">#&gt;   (tobramycin), AMK (amikacin), and KAN (kanamycin)</span></span>
 <span><span class="co">#&gt; ℹ For `polymyxins()` using column COL (colistin)</span></span>
 <span><span class="co">#&gt; Warning: There was 1 warning in `summarise()`.</span></span>
-<span><span class="co">#&gt; ℹ In argument: `across(c(aminoglycosides(), polymyxins()), resistance)`.</span></span>
+<span><span class="co">#&gt; ℹ In argument: `across(c(aminoglycosides(), polymyxins()),</span></span>
+<span><span class="co">#&gt;   resistance)`.</span></span>
 <span><span class="co">#&gt; ℹ In group 3: `ward = "Outpatient"`.</span></span>
 <span><span class="co">#&gt; Caused by warning:</span></span>
-<span><span class="co">#&gt; ! Introducing NA: only 23 results available for KAN in group: ward = "Outpatient"</span></span>
-<span><span class="co">#&gt; (whilst `minimum = 30`).</span></span>
+<span><span class="co">#&gt; ! Introducing NA: only 23 results available for KAN in group:</span></span>
+<span><span class="co">#&gt; ward = "Outpatient" (whilst `minimum = 30`).</span></span>
 <span><span class="va">out</span></span>
 <span><span class="co">#&gt; # A tibble: 3 × 6</span></span>
 <span><span class="co">#&gt;   ward         GEN   TOB   AMK   KAN   COL</span></span>
@@ -445,11 +451,12 @@
 <code class="sourceCode R"><span><span class="co"># transform the antibiotic columns to names:</span></span>
 <span><span class="va">out</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> <span class="fu"><a href="reference/ab_property.html">set_ab_names</a></span><span class="op">(</span><span class="op">)</span></span>
 <span><span class="co">#&gt; # A tibble: 3 × 6</span></span>
-<span><span class="co">#&gt;   ward       gentamicin tobramycin amikacin kanamycin colistin</span></span>
-<span><span class="co">#&gt;   &lt;chr&gt;           &lt;dbl&gt;      &lt;dbl&gt;    &lt;dbl&gt;     &lt;dbl&gt;    &lt;dbl&gt;</span></span>
-<span><span class="co">#&gt; 1 Clinical        0.229      0.315    0.626         1    0.780</span></span>
-<span><span class="co">#&gt; 2 ICU             0.290      0.400    0.662         1    0.857</span></span>
-<span><span class="co">#&gt; 3 Outpatient      0.2        0.368    0.605        NA    0.889</span></span></code></pre></div>
+<span><span class="co">#&gt;   ward       gentamicin tobramycin amikacin kanamycin</span></span>
+<span><span class="co">#&gt;   &lt;chr&gt;           &lt;dbl&gt;      &lt;dbl&gt;    &lt;dbl&gt;     &lt;dbl&gt;</span></span>
+<span><span class="co">#&gt; 1 Clinical        0.229      0.315    0.626         1</span></span>
+<span><span class="co">#&gt; 2 ICU             0.290      0.400    0.662         1</span></span>
+<span><span class="co">#&gt; 3 Outpatient      0.2        0.368    0.605        NA</span></span>
+<span><span class="co">#&gt; # ℹ 1 more variable: colistin &lt;dbl&gt;</span></span></code></pre></div>
 <div class="sourceCode" id="cb9"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="co"># transform the antibiotic column to ATC codes:</span></span>
 <span><span class="va">out</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> <span class="fu"><a href="reference/ab_property.html">set_ab_names</a></span><span class="op">(</span>property <span class="op">=</span> <span class="st">"atc"</span><span class="op">)</span></span>
--- a/index.md
+++ b/index.md
@@ -100,6 +100,7 @@ selectors](https://amr-for-r.org/reference/antimicrobial_selectors.html),
 which work in base R, `dplyr` and `data.table`.

 ``` r
+
 # AMR works great with dplyr, but it's not required or neccesary
 library(AMR)
 library(dplyr, warn.conflicts = FALSE)
@@ -116,24 +117,26 @@ example_isolates %>%
 #> ℹ Using column mo as input for `mo_fullname()`
 #> ℹ Using column mo as input for `mo_is_gram_negative()`
 #> ℹ Using column mo as input for `mo_is_intrinsic_resistant()`
-#> ℹ Determining intrinsic resistance based on 'EUCAST Expected Resistant
-#>   Phenotypes' v1.2 (2023). This note will be shown once per session.
-#> ℹ For `aminoglycosides()` using columns GEN (gentamicin), TOB (tobramycin), AMK
-#>   (amikacin), and KAN (kanamycin)
-#> ℹ For `carbapenems()` using columns IPM (imipenem) and MEM (meropenem)
+#> ℹ Determining intrinsic resistance based on 'EUCAST Expected
+#>   Resistant Phenotypes' v1.2 (2023). This note will be shown
+#>   once per session.
+#> ℹ For `aminoglycosides()` using columns GEN (gentamicin), TOB
+#>   (tobramycin), AMK (amikacin), and KAN (kanamycin)
+#> ℹ For `carbapenems()` using columns IPM (imipenem) and MEM
+#>   (meropenem)
 #> # A tibble: 35 × 7
 #>    bacteria         GEN   TOB   AMK   KAN   IPM   MEM  
 #>    <chr>            <sir> <sir> <sir> <sir> <sir> <sir>
-#>  1 Pseudomonas aeruginosa       I     S     NA    R     S     NA   
-#>  2 Pseudomonas aeruginosa       I     S     NA    R     S     NA   
-#>  3 Pseudomonas aeruginosa       I     S     NA    R     S     NA   
-#>  4 Pseudomonas aeruginosa       S     S     S     R     NA    S    
-#>  5 Pseudomonas aeruginosa       S     S     S     R     S     S    
-#>  6 Pseudomonas aeruginosa       S     S     S     R     S     S    
-#>  7 Stenotrophomonas maltophilia R     R     R     R     R     R    
-#>  8 Pseudomonas aeruginosa       S     S     S     R     NA    S    
-#>  9 Pseudomonas aeruginosa       S     S     S     R     NA    S    
-#> 10 Pseudomonas aeruginosa       S     S     S     R     S     S    
+#>  1 Pseudomonas aer… I     S     NA    R     S     NA   
+#>  2 Pseudomonas aer… I     S     NA    R     S     NA   
+#>  3 Pseudomonas aer… I     S     NA    R     S     NA   
+#>  4 Pseudomonas aer… S     S     S     R     NA    S    
+#>  5 Pseudomonas aer… S     S     S     R     S     S    
+#>  6 Pseudomonas aer… S     S     S     R     S     S    
+#>  7 Stenotrophomona… R     R     R     R     R     R    
+#>  8 Pseudomonas aer… S     S     S     R     NA    S    
+#>  9 Pseudomonas aer… S     S     S     R     NA    S    
+#> 10 Pseudomonas aer… S     S     S     R     S     S    
 #> # ℹ 25 more rows
 ```

@@ -161,15 +164,17 @@ If used inside [R Markdown](https://rmarkdown.rstudio.com) or
 output format automatically (such as markdown, LaTeX, HTML, etc.).

 ``` r
+
 antibiogram(example_isolates,
            antimicrobials = c(aminoglycosides(), carbapenems()))
-#> ℹ For `aminoglycosides()` using columns GEN (gentamicin), TOB (tobramycin), AMK
-#>   (amikacin), and KAN (kanamycin)
-#> ℹ For `carbapenems()` using columns IPM (imipenem) and MEM (meropenem)
+#> ℹ For `aminoglycosides()` using columns GEN (gentamicin), TOB
+#>   (tobramycin), AMK (amikacin), and KAN (kanamycin)
+#> ℹ For `carbapenems()` using columns IPM (imipenem) and MEM
+#>   (meropenem)
 ```

 | Pathogen | Amikacin | Gentamicin | Imipenem | Kanamycin | Meropenem | Tobramycin |
-|:-----------------|:---------------------|:--------------------|:---------------------|:----------------|:---------------------|:--------------------|
+|:---|:---|:---|:---|:---|:---|:---|
 | CoNS | 0% (0-8%,N=43) | 86% (82-90%,N=309) | 52% (37-67%,N=48) | 0% (0-8%,N=43) | 52% (37-67%,N=48) | 22% (12-35%,N=55) |
 | *E. coli* | 100% (98-100%,N=171) | 98% (96-99%,N=460) | 100% (99-100%,N=422) | NA | 100% (99-100%,N=418) | 97% (96-99%,N=462) |
 | *E. faecalis* | 0% (0-9%,N=39) | 0% (0-9%,N=39) | 100% (91-100%,N=38) | 0% (0-9%,N=39) | NA | 0% (0-9%,N=39) |
@@ -185,13 +190,14 @@ In combination antibiograms, it is clear that combined antimicrobials
 yield higher empiric coverage:

 ``` r
+
 antibiogram(example_isolates,
            antimicrobials = c("TZP", "TZP+TOB", "TZP+GEN"),
            mo_transform = "gramstain")
 ```

 | Pathogen | Piperacillin/tazobactam | Piperacillin/tazobactam + Gentamicin | Piperacillin/tazobactam + Tobramycin |
-|:--------------|:------------------------|:-------------------------------------|:-------------------------------------|
+|:---|:---|:---|:---|
 | Gram-negative | 88% (85-91%,N=641) | 99% (97-99%,N=691) | 98% (97-99%,N=693) |
 | Gram-positive | 86% (82-89%,N=345) | 98% (96-98%,N=1044) | 95% (93-97%,N=550) |

@@ -201,6 +207,7 @@ with support for 28 languages that are often detected automatically
 based on system language:

 ``` r
+
 antibiogram(example_isolates,
            antimicrobials = c("cipro", "tobra", "genta"), # any arbitrary name or code will work
            mo_transform = "gramstain",
@@ -221,6 +228,7 @@ with new scale functions, to allow plotting of log2-distributed MIC
 values and SIR values.

 ``` r
+
 library(ggplot2)
 library(AMR)

@@ -258,6 +266,7 @@ For a manual approach, you can use the `resistance` or
 function:

 ``` r
+
 example_isolates %>%
  # group by ward:
  group_by(ward) %>%
@@ -266,16 +275,18 @@ example_isolates %>%
  summarise(across(c(GEN, TOB),
                   list(total_R = resistance,
                        conf_int = function(x) sir_confidence_interval(x, collapse = "-"))))
-#> ℹ `resistance()` assumes the EUCAST guideline and thus considers the 'I'
-#>   category susceptible. Set the `guideline` argument or the `AMR_guideline`
-#>   option to either "CLSI" or "EUCAST", see `?AMR-options`.
+#> ℹ `resistance()` assumes the EUCAST guideline and thus
+#>   considers the 'I' category susceptible. Set the `guideline`
+#>   argument or the `AMR_guideline` option to either "CLSI" or
+#>   "EUCAST", see `?AMR-options`.
 #> ℹ This message will be shown once per session.
 #> # A tibble: 3 × 5
-#>   ward       GEN_total_R GEN_conf_int TOB_total_R TOB_conf_int
-#>   <chr>            <dbl> <chr>              <dbl> <chr>       
-#> 1 Clinical         0.229 0.205-0.254        0.315 0.284-0.347 
-#> 2 ICU              0.290 0.253-0.33         0.400 0.353-0.449 
-#> 3 Outpatient       0.2   0.131-0.285        0.368 0.254-0.493
+#>   ward       GEN_total_R GEN_conf_int TOB_total_R
+#>   <chr>            <dbl> <chr>              <dbl>
+#> 1 Clinical         0.229 0.205-0.254        0.315
+#> 2 ICU              0.290 0.253-0.33         0.400
+#> 3 Outpatient       0.2   0.131-0.285        0.368
+#> # ℹ 1 more variable: TOB_conf_int <chr>
 ```

 Or use [antimicrobial
@@ -283,6 +294,7 @@ selectors](https://amr-for-r.org/reference/antimicrobial_selectors.html)
 to select a series of antibiotic columns:

 ``` r
+
 library(AMR)
 library(dplyr)

@@ -292,15 +304,16 @@ out <- example_isolates %>%
  # calculate AMR using resistance(), over all aminoglycosides and polymyxins:
  summarise(across(c(aminoglycosides(), polymyxins()),
            resistance))
-#> ℹ For `aminoglycosides()` using columns GEN (gentamicin), TOB (tobramycin), AMK
-#>   (amikacin), and KAN (kanamycin)
+#> ℹ For `aminoglycosides()` using columns GEN (gentamicin), TOB
+#>   (tobramycin), AMK (amikacin), and KAN (kanamycin)
 #> ℹ For `polymyxins()` using column COL (colistin)
 #> Warning: There was 1 warning in `summarise()`.
-#> ℹ In argument: `across(c(aminoglycosides(), polymyxins()), resistance)`.
+#> ℹ In argument: `across(c(aminoglycosides(), polymyxins()),
+#>   resistance)`.
 #> ℹ In group 3: `ward = "Outpatient"`.
 #> Caused by warning:
-#> ! Introducing NA: only 23 results available for KAN in group: ward = "Outpatient"
-#> (whilst `minimum = 30`).
+#> ! Introducing NA: only 23 results available for KAN in group:
+#> ward = "Outpatient" (whilst `minimum = 30`).
 out
 #> # A tibble: 3 × 6
 #>   ward         GEN   TOB   AMK   KAN   COL
@@ -311,17 +324,20 @@ out
 ```

 ``` r
+
 # transform the antibiotic columns to names:
 out %>% set_ab_names()
 #> # A tibble: 3 × 6
-#>   ward       gentamicin tobramycin amikacin kanamycin colistin
-#>   <chr>           <dbl>      <dbl>    <dbl>     <dbl>    <dbl>
-#> 1 Clinical        0.229      0.315    0.626         1    0.780
-#> 2 ICU             0.290      0.400    0.662         1    0.857
-#> 3 Outpatient      0.2        0.368    0.605        NA    0.889
+#>   ward       gentamicin tobramycin amikacin kanamycin
+#>   <chr>           <dbl>      <dbl>    <dbl>     <dbl>
+#> 1 Clinical        0.229      0.315    0.626         1
+#> 2 ICU             0.290      0.400    0.662         1
+#> 3 Outpatient      0.2        0.368    0.605        NA
+#> # ℹ 1 more variable: colistin <dbl>
 ```

 ``` r
+
 # transform the antibiotic column to ATC codes:
 out %>% set_ab_names(property = "atc")
 #> # A tibble: 3 × 6
@@ -393,6 +409,7 @@ This package is available [here on the official R network
 R from CRAN by using the command:

 ``` r
+
 install.packages("AMR")
 ```

@@ -417,6 +434,7 @@ here](https://github.com/msberends/AMR/wiki/Developer-Guideline).
 To install the latest and unpublished beta version:

 ``` r
+
 install.packages("AMR", repos = "beta.amr-for-r.org")

 # if this does not work, try to install directly from GitHub using the 'remotes' package:
--- a/llms.txt
+++ b/llms.txt
@@ -100,6 +100,7 @@ selectors](https://amr-for-r.org/reference/antimicrobial_selectors.html),
 which work in base R, `dplyr` and `data.table`.

 ``` r
+
 # AMR works great with dplyr, but it's not required or neccesary
 library(AMR)
 library(dplyr, warn.conflicts = FALSE)
@@ -116,24 +117,26 @@ example_isolates %>%
 #> ℹ Using column mo as input for `mo_fullname()`
 #> ℹ Using column mo as input for `mo_is_gram_negative()`
 #> ℹ Using column mo as input for `mo_is_intrinsic_resistant()`
-#> ℹ Determining intrinsic resistance based on 'EUCAST Expected Resistant
-#>   Phenotypes' v1.2 (2023). This note will be shown once per session.
-#> ℹ For `aminoglycosides()` using columns GEN (gentamicin), TOB (tobramycin), AMK
-#>   (amikacin), and KAN (kanamycin)
-#> ℹ For `carbapenems()` using columns IPM (imipenem) and MEM (meropenem)
+#> ℹ Determining intrinsic resistance based on 'EUCAST Expected
+#>   Resistant Phenotypes' v1.2 (2023). This note will be shown
+#>   once per session.
+#> ℹ For `aminoglycosides()` using columns GEN (gentamicin), TOB
+#>   (tobramycin), AMK (amikacin), and KAN (kanamycin)
+#> ℹ For `carbapenems()` using columns IPM (imipenem) and MEM
+#>   (meropenem)
 #> # A tibble: 35 × 7
 #>    bacteria         GEN   TOB   AMK   KAN   IPM   MEM  
 #>    <chr>            <sir> <sir> <sir> <sir> <sir> <sir>
-#>  1 Pseudomonas aeruginosa       I     S     NA    R     S     NA   
-#>  2 Pseudomonas aeruginosa       I     S     NA    R     S     NA   
-#>  3 Pseudomonas aeruginosa       I     S     NA    R     S     NA   
-#>  4 Pseudomonas aeruginosa       S     S     S     R     NA    S    
-#>  5 Pseudomonas aeruginosa       S     S     S     R     S     S    
-#>  6 Pseudomonas aeruginosa       S     S     S     R     S     S    
-#>  7 Stenotrophomonas maltophilia R     R     R     R     R     R    
-#>  8 Pseudomonas aeruginosa       S     S     S     R     NA    S    
-#>  9 Pseudomonas aeruginosa       S     S     S     R     NA    S    
-#> 10 Pseudomonas aeruginosa       S     S     S     R     S     S    
+#>  1 Pseudomonas aer… I     S     NA    R     S     NA   
+#>  2 Pseudomonas aer… I     S     NA    R     S     NA   
+#>  3 Pseudomonas aer… I     S     NA    R     S     NA   
+#>  4 Pseudomonas aer… S     S     S     R     NA    S    
+#>  5 Pseudomonas aer… S     S     S     R     S     S    
+#>  6 Pseudomonas aer… S     S     S     R     S     S    
+#>  7 Stenotrophomona… R     R     R     R     R     R    
+#>  8 Pseudomonas aer… S     S     S     R     NA    S    
+#>  9 Pseudomonas aer… S     S     S     R     NA    S    
+#> 10 Pseudomonas aer… S     S     S     R     S     S    
 #> # ℹ 25 more rows
 ```

@@ -161,15 +164,17 @@ If used inside [R Markdown](https://rmarkdown.rstudio.com) or
 output format automatically (such as markdown, LaTeX, HTML, etc.).

 ``` r
+
 antibiogram(example_isolates,
            antimicrobials = c(aminoglycosides(), carbapenems()))
-#> ℹ For `aminoglycosides()` using columns GEN (gentamicin), TOB (tobramycin), AMK
-#>   (amikacin), and KAN (kanamycin)
-#> ℹ For `carbapenems()` using columns IPM (imipenem) and MEM (meropenem)
+#> ℹ For `aminoglycosides()` using columns GEN (gentamicin), TOB
+#>   (tobramycin), AMK (amikacin), and KAN (kanamycin)
+#> ℹ For `carbapenems()` using columns IPM (imipenem) and MEM
+#>   (meropenem)
 ```

 | Pathogen | Amikacin | Gentamicin | Imipenem | Kanamycin | Meropenem | Tobramycin |
-|:-----------------|:---------------------|:--------------------|:---------------------|:----------------|:---------------------|:--------------------|
+|:---|:---|:---|:---|:---|:---|:---|
 | CoNS | 0% (0-8%,N=43) | 86% (82-90%,N=309) | 52% (37-67%,N=48) | 0% (0-8%,N=43) | 52% (37-67%,N=48) | 22% (12-35%,N=55) |
 | *E. coli* | 100% (98-100%,N=171) | 98% (96-99%,N=460) | 100% (99-100%,N=422) | NA | 100% (99-100%,N=418) | 97% (96-99%,N=462) |
 | *E. faecalis* | 0% (0-9%,N=39) | 0% (0-9%,N=39) | 100% (91-100%,N=38) | 0% (0-9%,N=39) | NA | 0% (0-9%,N=39) |
@@ -185,13 +190,14 @@ In combination antibiograms, it is clear that combined antimicrobials
 yield higher empiric coverage:

 ``` r
+
 antibiogram(example_isolates,
            antimicrobials = c("TZP", "TZP+TOB", "TZP+GEN"),
            mo_transform = "gramstain")
 ```

 | Pathogen | Piperacillin/tazobactam | Piperacillin/tazobactam + Gentamicin | Piperacillin/tazobactam + Tobramycin |
-|:--------------|:------------------------|:-------------------------------------|:-------------------------------------|
+|:---|:---|:---|:---|
 | Gram-negative | 88% (85-91%,N=641) | 99% (97-99%,N=691) | 98% (97-99%,N=693) |
 | Gram-positive | 86% (82-89%,N=345) | 98% (96-98%,N=1044) | 95% (93-97%,N=550) |

@@ -201,6 +207,7 @@ with support for 28 languages that are often detected automatically
 based on system language:

 ``` r
+
 antibiogram(example_isolates,
            antimicrobials = c("cipro", "tobra", "genta"), # any arbitrary name or code will work
            mo_transform = "gramstain",
@@ -221,6 +228,7 @@ with new scale functions, to allow plotting of log2-distributed MIC
 values and SIR values.

 ``` r
+
 library(ggplot2)
 library(AMR)

@@ -258,6 +266,7 @@ For a manual approach, you can use the `resistance` or
 function:

 ``` r
+
 example_isolates %>%
  # group by ward:
  group_by(ward) %>%
@@ -266,16 +275,18 @@ example_isolates %>%
  summarise(across(c(GEN, TOB),
                   list(total_R = resistance,
                        conf_int = function(x) sir_confidence_interval(x, collapse = "-"))))
-#> ℹ `resistance()` assumes the EUCAST guideline and thus considers the 'I'
-#>   category susceptible. Set the `guideline` argument or the `AMR_guideline`
-#>   option to either "CLSI" or "EUCAST", see `?AMR-options`.
+#> ℹ `resistance()` assumes the EUCAST guideline and thus
+#>   considers the 'I' category susceptible. Set the `guideline`
+#>   argument or the `AMR_guideline` option to either "CLSI" or
+#>   "EUCAST", see `?AMR-options`.
 #> ℹ This message will be shown once per session.
 #> # A tibble: 3 × 5
-#>   ward       GEN_total_R GEN_conf_int TOB_total_R TOB_conf_int
-#>   <chr>            <dbl> <chr>              <dbl> <chr>       
-#> 1 Clinical         0.229 0.205-0.254        0.315 0.284-0.347 
-#> 2 ICU              0.290 0.253-0.33         0.400 0.353-0.449 
-#> 3 Outpatient       0.2   0.131-0.285        0.368 0.254-0.493
+#>   ward       GEN_total_R GEN_conf_int TOB_total_R
+#>   <chr>            <dbl> <chr>              <dbl>
+#> 1 Clinical         0.229 0.205-0.254        0.315
+#> 2 ICU              0.290 0.253-0.33         0.400
+#> 3 Outpatient       0.2   0.131-0.285        0.368
+#> # ℹ 1 more variable: TOB_conf_int <chr>
 ```

 Or use [antimicrobial
@@ -283,6 +294,7 @@ selectors](https://amr-for-r.org/reference/antimicrobial_selectors.html)
 to select a series of antibiotic columns:

 ``` r
+
 library(AMR)
 library(dplyr)

@@ -292,15 +304,16 @@ out <- example_isolates %>%
  # calculate AMR using resistance(), over all aminoglycosides and polymyxins:
  summarise(across(c(aminoglycosides(), polymyxins()),
            resistance))
-#> ℹ For `aminoglycosides()` using columns GEN (gentamicin), TOB (tobramycin), AMK
-#>   (amikacin), and KAN (kanamycin)
+#> ℹ For `aminoglycosides()` using columns GEN (gentamicin), TOB
+#>   (tobramycin), AMK (amikacin), and KAN (kanamycin)
 #> ℹ For `polymyxins()` using column COL (colistin)
 #> Warning: There was 1 warning in `summarise()`.
-#> ℹ In argument: `across(c(aminoglycosides(), polymyxins()), resistance)`.
+#> ℹ In argument: `across(c(aminoglycosides(), polymyxins()),
+#>   resistance)`.
 #> ℹ In group 3: `ward = "Outpatient"`.
 #> Caused by warning:
-#> ! Introducing NA: only 23 results available for KAN in group: ward = "Outpatient"
-#> (whilst `minimum = 30`).
+#> ! Introducing NA: only 23 results available for KAN in group:
+#> ward = "Outpatient" (whilst `minimum = 30`).
 out
 #> # A tibble: 3 × 6
 #>   ward         GEN   TOB   AMK   KAN   COL
@@ -311,17 +324,20 @@ out
 ```

 ``` r
+
 # transform the antibiotic columns to names:
 out %>% set_ab_names()
 #> # A tibble: 3 × 6
-#>   ward       gentamicin tobramycin amikacin kanamycin colistin
-#>   <chr>           <dbl>      <dbl>    <dbl>     <dbl>    <dbl>
-#> 1 Clinical        0.229      0.315    0.626         1    0.780
-#> 2 ICU             0.290      0.400    0.662         1    0.857
-#> 3 Outpatient      0.2        0.368    0.605        NA    0.889
+#>   ward       gentamicin tobramycin amikacin kanamycin
+#>   <chr>           <dbl>      <dbl>    <dbl>     <dbl>
+#> 1 Clinical        0.229      0.315    0.626         1
+#> 2 ICU             0.290      0.400    0.662         1
+#> 3 Outpatient      0.2        0.368    0.605        NA
+#> # ℹ 1 more variable: colistin <dbl>
 ```

 ``` r
+
 # transform the antibiotic column to ATC codes:
 out %>% set_ab_names(property = "atc")
 #> # A tibble: 3 × 6
@@ -393,6 +409,7 @@ This package is available [here on the official R network
 R from CRAN by using the command:

 ``` r
+
 install.packages("AMR")
 ```

@@ -417,6 +434,7 @@ here](https://github.com/msberends/AMR/wiki/Developer-Guideline).
 To install the latest and unpublished beta version:

 ``` r
+
 install.packages("AMR", repos = "beta.amr-for-r.org")

 # if this does not work, try to install directly from GitHub using the 'remotes' package:
--- a/news/index.html
+++ b/news/index.html
@@ -7,7 +7,7 @@

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -49,11 +49,17 @@
    </div>

    <div class="section level2">
-<h2 class="pkg-version" data-toc-text="3.0.1.9052" id="amr-3019052">AMR 3.0.1.9052<a class="anchor" aria-label="anchor" href="#amr-3019052"></a></h2>
+<h2 class="pkg-version" data-toc-text="3.0.1.9053" id="amr-3019053">AMR 3.0.1.9053<a class="anchor" aria-label="anchor" href="#amr-3019053"></a></h2>
+<p>This will become release v3.1.0, intended for launch end of May.</p>
 <div class="section level4">
-<h4 id="new-3-0-1-9052">New<a class="anchor" aria-label="anchor" href="#new-3-0-1-9052"></a></h4>
+<h4 id="new-3-0-1-9053">New<a class="anchor" aria-label="anchor" href="#new-3-0-1-9053"></a></h4>
 <ul><li>Support for clinical breakpoints of 2026 of both CLSI and EUCAST, by adding all of their over 5,700 new clinical breakpoints to the <code>clinical_breakpoints</code> data set for usage in <code><a href="../reference/as.sir.html">as.sir()</a></code>. EUCAST 2026 is now the new default guideline for all MIC and disk diffusion interpretations.</li>
-<li>Integration with the <strong>tidymodels</strong> framework to allow seamless use of SIR, MIC and disk data in modelling pipelines via <code>recipes</code>
+<li>Support for the <a href="https://future.futureverse.org" class="external-link"><code>future</code></a> package and its framework, as the previous implementation of parallel computing was slow
+<ul><li>
+<strong>Breaking change</strong>: <code><a href="../reference/as.sir.html">as.sir()</a></code> with <code>parallel = TRUE</code> now requires a non-sequential <code><a href="https://future.futureverse.org/reference/plan.html" class="external-link">future::plan()</a></code> to be active before the call — e.g., <code>future::plan(future::multisession)</code> — and throws an informative error if none is set.</li>
+<li>New all-core usage setup: when the number of AB columns is smaller than the number of available cores, rows are now split into batches so all cores stay active (row-batch mode). Previously, a 6-column dataset on a 16-core machine would only use 6 cores; now all 16 are used, with each worker processing a smaller row slice (lower per-worker memory pressure and processing time)</li>
+</ul></li>
+<li>Integration with the <em>tidymodels</em> framework to allow seamless use of SIR, MIC and disk data in modelling pipelines via <code>recipes</code>
 <ul><li>
 <code><a href="../reference/amr-tidymodels.html">step_mic_log2()</a></code> to transform <code>&lt;mic&gt;</code> columns with log2, and <code><a href="../reference/amr-tidymodels.html">step_sir_numeric()</a></code> to convert <code>&lt;sir&gt;</code> columns to numeric</li>
 <li>New <code>tidyselect</code> helpers:
@@ -86,9 +92,8 @@
 <li>Two new <code>NA</code> objects, <code>NA_ab_</code> and <code>NA_mo_</code>, analogous to base R’s <code>NA_character_</code> and <code>NA_integer_</code>, for use in pipelines that require typed missing values</li>
 </ul></div>
 <div class="section level4">
-<h4 id="fixes-3-0-1-9052">Fixes<a class="anchor" aria-label="anchor" href="#fixes-3-0-1-9052"></a></h4>
-<ul><li>Fixed multiple bugs in the <code>parallel = TRUE</code> mode of <code><a href="../reference/as.sir.html">as.sir()</a></code> for data frames</li>
-<li>Fixed a bug in <code><a href="../reference/as.sir.html">as.sir()</a></code> where values that were purely numeric (e.g., <code>"1"</code>) and matched the broad SIR-matching regex would be incorrectly stripped of all content by the Unicode letter filter</li>
+<h4 id="fixes-3-0-1-9053">Fixes<a class="anchor" aria-label="anchor" href="#fixes-3-0-1-9053"></a></h4>
+<ul><li>Fixed a bug in <code><a href="../reference/as.sir.html">as.sir()</a></code> where values that were purely numeric (e.g., <code>"1"</code>) and matched the broad SIR-matching regex would be incorrectly stripped of all content by the Unicode letter filter</li>
 <li>Fixed a bug in <code><a href="../reference/as.mic.html">as.mic()</a></code> where MIC values in scientific notation (e.g., <code>"1e-3"</code>) were incorrectly handled because the letter <code>e</code> was removed along with other Unicode letters; scientific notation <code>e</code> is now preserved</li>
 <li>Fixed a bug in <code><a href="../reference/as.ab.html">as.ab()</a></code> where certain AB codes containing “PH” or “TH” (such as <code>ETH</code>, <code>MTH</code>, <code>PHE</code>, <code>PHN</code>, <code>STH</code>, <code>THA</code>, <code>THI1</code>) would incorrectly return <code>NA</code> when combined in a vector with any untranslatable value (<a href="https://github.com/msberends/AMR/issues/245" class="external-link">#245</a>)</li>
 <li>Fixed a bug in <code><a href="../reference/antibiogram.html">antibiogram()</a></code> for when no antimicrobials are set</li>
@@ -104,12 +109,10 @@
 <li>Fixed BRMO classification by including bacterial complexes (<a href="https://github.com/msberends/AMR/issues/275" class="external-link">#275</a>)</li>
 <li>Fixed <code><a href="../reference/as.sir.html">as.sir()</a></code> for data frames silently deleting columns whose AB class was already <code>&lt;sir&gt;</code> when called a second time (re-running on already-converted data) (<a href="https://github.com/msberends/AMR/issues/278" class="external-link">#278</a>)</li>
 <li>Fixed <code><a href="../reference/as.sir.html">as.sir()</a></code> for data frames incorrectly treating metadata columns (e.g. <code>patient</code>, <code>ward</code>) as antibiotic columns when their names coincidentally matched an antibiotic code; column content is now validated against AMR data patterns before inclusion</li>
-<li>Improved parallel computing in <code><a href="../reference/as.sir.html">as.sir()</a></code>: when the number of AB columns is smaller than the number of available cores, rows are now split into batches so all cores stay active (row-batch mode). Previously, a 6-column dataset on a 16-core machine would only use 6 cores; now all 16 are used, with each worker processing a smaller row slice (lower per-worker memory pressure)</li>
-<li>Fixed <code><a href="../reference/as.sir.html">as.sir()</a></code> ignoring <code>info = FALSE</code> for columns with no breakpoints (e.g. cefoxitin against <em>E. coli</em>): an operator-precedence bug (<code>&amp;&amp;</code>/<code>||</code>) caused the “Interpreting MIC values” intro message to fire unconditionally when <code>nrow(breakpoints) == 0</code>, regardless of <code>info</code>; the progress bar title was also not gated by <code>info</code>
-</li>
+<li>Fixed <code><a href="../reference/as.sir.html">as.sir()</a></code> ignoring <code>info = FALSE</code> for columns with no breakpoints (e.g. cefoxitin against <em>E. coli</em>)</li>
 </ul></div>
 <div class="section level4">
-<h4 id="updates-3-0-1-9052">Updates<a class="anchor" aria-label="anchor" href="#updates-3-0-1-9052"></a></h4>
+<h4 id="updates-3-0-1-9053">Updates<a class="anchor" aria-label="anchor" href="#updates-3-0-1-9053"></a></h4>
 <ul><li>
 <code><a href="../reference/as.sir.html">as.sir()</a></code> with <code>reference_data</code>: custom guideline names now correctly classify values as R using EUCAST convention (<code>&gt; breakpoint_R</code> for MIC, <code>&lt; breakpoint_R</code> for disk); custom breakpoints with <code>host = NA</code> now serve as a host-agnostic fallback when no host-specific row matches (<a href="https://github.com/msberends/AMR/issues/239" class="external-link">#239</a>)</li>
 <li>Extensive <code>cli</code> integration for better message handling and clickable links in messages and warnings (<a href="https://github.com/msberends/AMR/issues/191" class="external-link">#191</a>, <a href="https://github.com/msberends/AMR/issues/265" class="external-link">#265</a>)</li>
@@ -134,7 +137,6 @@
 </ul></li>
 <li>
 <code><a href="../reference/ab_property.html">ab_group()</a></code> now returns values consist with the AMR selectors (<a href="https://github.com/msberends/AMR/issues/246" class="external-link">#246</a>)</li>
-<li>Added two new <code>NA</code> objects, <code>NA_ab_</code> and <code>NA_mo_</code>, analogous to base R’s <code>NA_character_</code> and <code>NA_integer_</code>, for use in pipelines that require typed missing values</li>
 </ul></div>
 </div>
    <div class="section level2">
--- a/news/index.md
+++ b/news/index.md
@@ -1,6 +1,8 @@
 # Changelog

-## AMR 3.0.1.9052
+## AMR 3.0.1.9053
+
+This will become release v3.1.0, intended for launch end of May.

 #### New

@@ -10,7 +12,23 @@
  [`as.sir()`](https://amr-for-r.org/reference/as.sir.md). EUCAST 2026
  is now the new default guideline for all MIC and disk diffusion
  interpretations.
- Integration with the **tidymodels** framework to allow seamless use of
+- Support for the [`future`](https://future.futureverse.org) package and
+  its framework, as the previous implementation of parallel computing
+  was slow
+  - **Breaking change**:
+    [`as.sir()`](https://amr-for-r.org/reference/as.sir.md) with
+    `parallel = TRUE` now requires a non-sequential
+    [`future::plan()`](https://future.futureverse.org/reference/plan.html)
+    to be active before the call — e.g.,
+    `future::plan(future::multisession)` — and throws an informative
+    error if none is set.
+  - New all-core usage setup: when the number of AB columns is smaller
+    than the number of available cores, rows are now split into batches
+    so all cores stay active (row-batch mode). Previously, a 6-column
+    dataset on a 16-core machine would only use 6 cores; now all 16 are
+    used, with each worker processing a smaller row slice (lower
+    per-worker memory pressure and processing time)
+- Integration with the *tidymodels* framework to allow seamless use of
  SIR, MIC and disk data in modelling pipelines via `recipes`
  - [`step_mic_log2()`](https://amr-for-r.org/reference/amr-tidymodels.md)
    to transform `<mic>` columns with log2, and
@@ -63,9 +81,6 @@

 #### Fixes

- Fixed multiple bugs in the `parallel = TRUE` mode of
-  [`as.sir()`](https://amr-for-r.org/reference/as.sir.md) for data
-  frames
 - Fixed a bug in [`as.sir()`](https://amr-for-r.org/reference/as.sir.md)
  where values that were purely numeric (e.g., `"1"`) and matched the
  broad SIR-matching regex would be incorrectly stripped of all content
@@ -111,19 +126,9 @@
  as antibiotic columns when their names coincidentally matched an
  antibiotic code; column content is now validated against AMR data
  patterns before inclusion
- Improved parallel computing in
-  [`as.sir()`](https://amr-for-r.org/reference/as.sir.md): when the
-  number of AB columns is smaller than the number of available cores,
-  rows are now split into batches so all cores stay active (row-batch
-  mode). Previously, a 6-column dataset on a 16-core machine would only
-  use 6 cores; now all 16 are used, with each worker processing a
-  smaller row slice (lower per-worker memory pressure)
 - Fixed [`as.sir()`](https://amr-for-r.org/reference/as.sir.md) ignoring
  `info = FALSE` for columns with no breakpoints (e.g. cefoxitin against
-  *E. coli*): an operator-precedence bug (`&&`/`||`) caused the
-  “Interpreting MIC values” intro message to fire unconditionally when
-  `nrow(breakpoints) == 0`, regardless of `info`; the progress bar title
-  was also not gated by `info`
+  *E. coli*)

 #### Updates

@@ -184,9 +189,6 @@
 - [`ab_group()`](https://amr-for-r.org/reference/ab_property.md) now
  returns values consist with the AMR selectors
  ([\#246](https://github.com/msberends/AMR/issues/246))
- Added two new `NA` objects, `NA_ab_` and `NA_mo_`, analogous to base
-  R’s `NA_character_` and `NA_integer_`, for use in pipelines that
-  require typed missing values

 ## AMR 3.0.1

--- a/pkgdown.yml
+++ b/pkgdown.yml
@@ -1,4 +1,4 @@
-pandoc: 3.1.11
+pandoc: 3.8.3
 pkgdown: 2.2.0
 pkgdown_sha: ~
 articles:
@@ -10,7 +10,7 @@ articles:
  PCA: PCA.html
  WHONET: WHONET.html
  WISCA: WISCA.html
-last_built: 2026-04-25T14:24Z
+last_built: 2026-04-30T08:02Z
 urls:
  reference: https://amr-for-r.org/reference
  article: https://amr-for-r.org/articles
--- a/reference/AMR-deprecated.html
+++ b/reference/AMR-deprecated.html
@@ -7,7 +7,7 @@

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/reference/AMR-options.html
+++ b/reference/AMR-options.html
@@ -9,7 +9,7 @@ options(AMR_guideline = "CLSI")'><meta property="og:image" content="https://amr-

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/reference/AMR.html
+++ b/reference/AMR.html
@@ -21,7 +21,7 @@ The AMR package is available in English, Arabic, Bengali, Chinese, Czech, Danish

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/reference/AMR.md
+++ b/reference/AMR.md
@@ -57,6 +57,7 @@ Data." *Journal of Statistical Software*, *104*(3), 1-31.

 A BibTeX entry for LaTeX users is:

+
    @Article{,
      title = {{AMR}: An {R} Package for Working with Antimicrobial Resistance Data},
      author = {Matthijs S. Berends and Christian F. Luz and Alexander W. Friedrich and Bhanu N. M. Sinha and Casper J. Albers and Corinna Glasner},
--- a/reference/WHOCC.html
+++ b/reference/WHOCC.html
@@ -7,7 +7,7 @@

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/reference/WHONET.html
+++ b/reference/WHONET.html
@@ -7,7 +7,7 @@

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/reference/ab_from_text.html
+++ b/reference/ab_from_text.html
@@ -7,7 +7,7 @@

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/reference/ab_property.html
+++ b/reference/ab_property.html
@@ -7,7 +7,7 @@

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/reference/add_custom_antimicrobials.html
+++ b/reference/add_custom_antimicrobials.html
@@ -7,7 +7,7 @@

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/reference/add_custom_microorganisms.html
+++ b/reference/add_custom_microorganisms.html
@@ -7,7 +7,7 @@

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/reference/age.html
+++ b/reference/age.html
@@ -7,7 +7,7 @@

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -112,16 +112,16 @@
 <span class="r-in"><span></span></span>
 <span class="r-in"><span><span class="va">df</span></span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>    birth_date age age_exact age_at_y2k</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 1  1999-06-30  26  26.81918          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 2  1968-01-29  58  58.23562         31</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 3  1965-12-05  60  60.38630         34</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 4  1980-03-01  46  46.15068         19</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 5  1949-11-01  76  76.47945         50</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 6  1947-02-14  79  79.19178         52</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 7  1940-02-19  86  86.17808         59</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 8  1988-01-10  38  38.28767         11</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 9  1997-08-27  28  28.66027          2</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 10 1978-01-26  48  48.24384         21</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> 1  1999-06-30  26  26.83288          0</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> 2  1968-01-29  58  58.24932         31</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> 3  1965-12-05  60  60.40000         34</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> 4  1980-03-01  46  46.16438         19</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> 5  1949-11-01  76  76.49315         50</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> 6  1947-02-14  79  79.20548         52</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> 7  1940-02-19  86  86.19178         59</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> 8  1988-01-10  38  38.30137         11</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> 9  1997-08-27  28  28.67397          2</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> 10 1978-01-26  48  48.25753         21</span>
 </code></pre></div>
    </div>
  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
--- a/reference/age.md
+++ b/reference/age.md
@@ -81,14 +81,14 @@ df$age_at_y2k <- age(df$birth_date, "2000-01-01")

 df
 #>    birth_date age age_exact age_at_y2k
-#> 1  1999-06-30  26  26.81918          0
-#> 2  1968-01-29  58  58.23562         31
-#> 3  1965-12-05  60  60.38630         34
-#> 4  1980-03-01  46  46.15068         19
-#> 5  1949-11-01  76  76.47945         50
-#> 6  1947-02-14  79  79.19178         52
-#> 7  1940-02-19  86  86.17808         59
-#> 8  1988-01-10  38  38.28767         11
-#> 9  1997-08-27  28  28.66027          2
-#> 10 1978-01-26  48  48.24384         21
+#> 1  1999-06-30  26  26.83288          0
+#> 2  1968-01-29  58  58.24932         31
+#> 3  1965-12-05  60  60.40000         34
+#> 4  1980-03-01  46  46.16438         19
+#> 5  1949-11-01  76  76.49315         50
+#> 6  1947-02-14  79  79.20548         52
+#> 7  1940-02-19  86  86.19178         59
+#> 8  1988-01-10  38  38.30137         11
+#> 9  1997-08-27  28  28.67397          2
+#> 10 1978-01-26  48  48.25753         21
 ```
--- a/reference/age_groups.html
+++ b/reference/age_groups.html
@@ -7,7 +7,7 @@

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/reference/amr-tidymodels.html
+++ b/reference/amr-tidymodels.html
@@ -7,7 +7,7 @@

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/reference/amr_course.html
+++ b/reference/amr_course.html
@@ -7,7 +7,7 @@

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/reference/antibiogram.html
+++ b/reference/antibiogram.html
@@ -9,7 +9,7 @@ Adhering to previously described approaches (see Source) and especially the Baye

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -411,7 +411,7 @@ Adhering to previously described approaches (see Source) and especially the Baye
 <span class="r-msg co"><span class="r-pr">#&gt;</span> <span style="color: #00BBBB;">ℹ</span> For `aminoglycosides()` using columns <span style="color: #00BB00; font-weight: bold;">GEN</span> (gentamicin), <span style="color: #00BB00; font-weight: bold;">TOB</span> (tobramycin), <span style="color: #00BB00; font-weight: bold;">AMK</span></span>
 <span class="r-msg co"><span class="r-pr">#&gt;</span>   (amikacin), and <span style="color: #00BB00; font-weight: bold;">KAN</span> (kanamycin)</span>
 <span class="r-msg co"><span class="r-pr">#&gt;</span> <span style="color: #00BBBB;">ℹ</span> For `carbapenems()` using columns <span style="color: #00BB00; font-weight: bold;">IPM</span> (imipenem) and <span style="color: #00BB00; font-weight: bold;">MEM</span> (meropenem)</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># An Antibiogram: 10 × 7</span></span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># An antibiogram: 10 × 7</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># Type:           Non-WISCA with 95% CI</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>    Pathogen       Amikacin    Gentamicin Imipenem Kanamycin Meropenem Tobramycin</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>          <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>       <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>      <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>     <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>     <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>     </span>
@@ -426,7 +426,7 @@ Adhering to previously described approaches (see Source) and especially the Baye
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span> S. hominis     <span style="color: #BB0000;">NA</span>          92% (84-9… <span style="color: #BB0000;">NA</span>       <span style="color: #BB0000;">NA</span>        <span style="color: #BB0000;">NA</span>        85% (74-9…</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span> S. pneumoniae  0% (0-3%,N… 0% (0-3%,… <span style="color: #BB0000;">NA</span>       0% (0-3%… <span style="color: #BB0000;">NA</span>        0% (0-3%,…</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># Use `ggplot2::autoplot()` or base R `plot()` to create a plot of this antibiogram,</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># or use it directly in R Markdown or https://quarto.org, see ?antibiogram</span></span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># or use it directly in R Markdown or Quarto, see ?antibiogram</span></span>
 <span class="r-in"><span></span></span>
 <span class="r-in"><span><span class="fu">antibiogram</span><span class="op">(</span><span class="va">example_isolates</span>,</span></span>
 <span class="r-in"><span>  antimicrobials <span class="op">=</span> <span class="fu"><a href="antimicrobial_selectors.html">aminoglycosides</a></span><span class="op">(</span><span class="op">)</span>,</span></span>
@@ -435,14 +435,14 @@ Adhering to previously described approaches (see Source) and especially the Baye
 <span class="r-in"><span><span class="op">)</span></span></span>
 <span class="r-msg co"><span class="r-pr">#&gt;</span> <span style="color: #00BBBB;">ℹ</span> For `aminoglycosides()` using columns <span style="color: #00BB00; font-weight: bold;">GEN</span> (gentamicin), <span style="color: #00BB00; font-weight: bold;">TOB</span> (tobramycin), <span style="color: #00BB00; font-weight: bold;">AMK</span></span>
 <span class="r-msg co"><span class="r-pr">#&gt;</span>   (amikacin), and <span style="color: #00BB00; font-weight: bold;">KAN</span> (kanamycin)</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># An Antibiogram: 2 × 5</span></span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># An antibiogram: 2 × 5</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># Type:           Non-WISCA with 95% CI</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>   Pathogen      J01GB01            J01GB03             J01GB04         J01GB06  </span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>         <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>              <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>               <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>           <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>    </span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span> Gram-negative 96% (94-97%,N=686) 96% (95-98%,N=684)  0% (0-10%,N=35) 98% (96-…</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span> Gram-positive 34% (31-38%,N=665) 63% (60-66%,N=1170) 0% (0-1%,N=436) 0% (0-1%…</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># Use `ggplot2::autoplot()` or base R `plot()` to create a plot of this antibiogram,</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># or use it directly in R Markdown or https://quarto.org, see ?antibiogram</span></span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># or use it directly in R Markdown or Quarto, see ?antibiogram</span></span>
 <span class="r-in"><span></span></span>
 <span class="r-in"><span><span class="fu">antibiogram</span><span class="op">(</span><span class="va">example_isolates</span>,</span></span>
 <span class="r-in"><span>  antimicrobials <span class="op">=</span> <span class="fu"><a href="antimicrobial_selectors.html">carbapenems</a></span><span class="op">(</span><span class="op">)</span>,</span></span>
@@ -450,7 +450,7 @@ Adhering to previously described approaches (see Source) and especially the Baye
 <span class="r-in"><span>  mo_transform <span class="op">=</span> <span class="st">"name"</span></span></span>
 <span class="r-in"><span><span class="op">)</span></span></span>
 <span class="r-msg co"><span class="r-pr">#&gt;</span> <span style="color: #00BBBB;">ℹ</span> For `carbapenems()` using columns <span style="color: #00BB00; font-weight: bold;">IPM</span> (imipenem) and <span style="color: #00BB00; font-weight: bold;">MEM</span> (meropenem)</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># An Antibiogram: 5 × 3</span></span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># An antibiogram: 5 × 3</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># Type:           Non-WISCA with 95% CI</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>   Pathogen                                 Imipenem             Meropenem       </span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>                                    <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>                <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>           </span>
@@ -460,7 +460,7 @@ Adhering to previously described approaches (see Source) and especially the Baye
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">4</span> Klebsiella pneumoniae                    100% (93-100%,N=51)  100% (93-100%,N…</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">5</span> Proteus mirabilis                        94% (79-99%,N=32)    <span style="color: #BB0000;">NA</span>              </span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># Use `ggplot2::autoplot()` or base R `plot()` to create a plot of this antibiogram,</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># or use it directly in R Markdown or https://quarto.org, see ?antibiogram</span></span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># or use it directly in R Markdown or Quarto, see ?antibiogram</span></span>
 <span class="r-in"><span></span></span>
 <span class="r-in"><span></span></span>
 <span class="r-in"><span><span class="co"># Combined antibiogram -------------------------------------------------</span></span></span>
@@ -470,7 +470,7 @@ Adhering to previously described approaches (see Source) and especially the Baye
 <span class="r-in"><span>  antimicrobials <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"TZP"</span>, <span class="st">"TZP+TOB"</span>, <span class="st">"TZP+GEN"</span><span class="op">)</span>,</span></span>
 <span class="r-in"><span>  mo_transform <span class="op">=</span> <span class="st">"gramstain"</span></span></span>
 <span class="r-in"><span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># An Antibiogram: 2 × 4</span></span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># An antibiogram: 2 × 4</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># Type:           Non-WISCA with 95% CI</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>   Pathogen  Piperacillin/tazobac…¹ Piperacillin/tazobac…² Piperacillin/tazobac…³</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>     <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>                  <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>                  <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>                 </span>
@@ -480,7 +480,7 @@ Adhering to previously described approaches (see Source) and especially the Baye
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;">#   ²`Piperacillin/tazobactam + Gentamicin`,</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;">#   ³`Piperacillin/tazobactam + Tobramycin`</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># Use `ggplot2::autoplot()` or base R `plot()` to create a plot of this antibiogram,</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># or use it directly in R Markdown or https://quarto.org, see ?antibiogram</span></span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># or use it directly in R Markdown or Quarto, see ?antibiogram</span></span>
 <span class="r-in"><span></span></span>
 <span class="r-in"><span><span class="co"># you can use any antimicrobial selector with `+` too:</span></span></span>
 <span class="r-in"><span><span class="fu">antibiogram</span><span class="op">(</span><span class="va">example_isolates</span>,</span></span>
@@ -488,7 +488,7 @@ Adhering to previously described approaches (see Source) and especially the Baye
 <span class="r-in"><span>  mo_transform <span class="op">=</span> <span class="st">"gramstain"</span></span></span>
 <span class="r-in"><span><span class="op">)</span></span></span>
 <span class="r-msg co"><span class="r-pr">#&gt;</span> <span style="color: #00BBBB;">ℹ</span> For `ureidopenicillins()` using column <span style="color: #00BB00; font-weight: bold;">TZP</span> (piperacillin/tazobactam)</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># An Antibiogram: 2 × 4</span></span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># An antibiogram: 2 × 4</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># Type:           Non-WISCA with 95% CI</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>   Pathogen  Piperacillin/tazobac…¹ Piperacillin/tazobac…² Piperacillin/tazobac…³</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>     <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>                  <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>                  <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>                 </span>
@@ -498,7 +498,7 @@ Adhering to previously described approaches (see Source) and especially the Baye
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;">#   ²`Piperacillin/tazobactam + Gentamicin`,</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;">#   ³`Piperacillin/tazobactam + Tobramycin`</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># Use `ggplot2::autoplot()` or base R `plot()` to create a plot of this antibiogram,</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># or use it directly in R Markdown or https://quarto.org, see ?antibiogram</span></span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># or use it directly in R Markdown or Quarto, see ?antibiogram</span></span>
 <span class="r-in"><span></span></span>
 <span class="r-in"><span><span class="co"># names of antimicrobials do not need to resemble columns exactly:</span></span></span>
 <span class="r-in"><span><span class="fu">antibiogram</span><span class="op">(</span><span class="va">example_isolates</span>,</span></span>
@@ -507,14 +507,14 @@ Adhering to previously described approaches (see Source) and especially the Baye
 <span class="r-in"><span>  ab_transform <span class="op">=</span> <span class="st">"name"</span>,</span></span>
 <span class="r-in"><span>  sep <span class="op">=</span> <span class="st">" &amp; "</span></span></span>
 <span class="r-in"><span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># An Antibiogram: 2 × 3</span></span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># An antibiogram: 2 × 3</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># Type:           Non-WISCA with 95% CI</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>   Pathogen      Ciprofloxacin      `Ciprofloxacin &amp; Gentamicin`</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>         <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>              <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>                       </span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span> Gram-negative 91% (88-93%,N=684) 99% (97-99%,N=694)          </span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span> Gram-positive 77% (74-80%,N=724) 93% (91-94%,N=847)          </span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># Use `ggplot2::autoplot()` or base R `plot()` to create a plot of this antibiogram,</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># or use it directly in R Markdown or https://quarto.org, see ?antibiogram</span></span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># or use it directly in R Markdown or Quarto, see ?antibiogram</span></span>
 <span class="r-in"><span></span></span>
 <span class="r-in"><span></span></span>
 <span class="r-in"><span><span class="co"># Syndromic antibiogram ------------------------------------------------</span></span></span>
@@ -527,7 +527,7 @@ Adhering to previously described approaches (see Source) and especially the Baye
 <span class="r-msg co"><span class="r-pr">#&gt;</span> <span style="color: #00BBBB;">ℹ</span> For `aminoglycosides()` using columns <span style="color: #00BB00; font-weight: bold;">GEN</span> (gentamicin), <span style="color: #00BB00; font-weight: bold;">TOB</span> (tobramycin), <span style="color: #00BB00; font-weight: bold;">AMK</span></span>
 <span class="r-msg co"><span class="r-pr">#&gt;</span>   (amikacin), and <span style="color: #00BB00; font-weight: bold;">KAN</span> (kanamycin)</span>
 <span class="r-msg co"><span class="r-pr">#&gt;</span> <span style="color: #00BBBB;">ℹ</span> For `carbapenems()` using columns <span style="color: #00BB00; font-weight: bold;">IPM</span> (imipenem) and <span style="color: #00BB00; font-weight: bold;">MEM</span> (meropenem)</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># An Antibiogram: 14 × 8</span></span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># An antibiogram: 14 × 8</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># Type:           Non-WISCA with 95% CI</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>    `Syndromic Group` Pathogen   Amikacin Gentamicin Imipenem Kanamycin Meropenem</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>             <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>      <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>      <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>     <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>    </span>
@@ -547,7 +547,7 @@ Adhering to previously described approaches (see Source) and especially the Baye
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">14</span> ICU               S. pneumo… 0% (0-1… 0% (0-12%… <span style="color: #BB0000;">NA</span>       0% (0-12… <span style="color: #BB0000;">NA</span>       </span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 1 more variable: Tobramycin &lt;chr&gt;</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># Use `ggplot2::autoplot()` or base R `plot()` to create a plot of this antibiogram,</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># or use it directly in R Markdown or https://quarto.org, see ?antibiogram</span></span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># or use it directly in R Markdown or Quarto, see ?antibiogram</span></span>
 <span class="r-in"><span></span></span>
 <span class="r-in"><span><span class="co"># now define a data set with only E. coli</span></span></span>
 <span class="r-in"><span><span class="va">ex1</span> <span class="op">&lt;-</span> <span class="va">example_isolates</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/which.html" class="external-link">which</a></span><span class="op">(</span><span class="fu"><a href="mo_property.html">mo_genus</a></span><span class="op">(</span><span class="op">)</span> <span class="op">==</span> <span class="st">"Escherichia"</span><span class="op">)</span>, <span class="op">]</span></span></span>
@@ -565,14 +565,14 @@ Adhering to previously described approaches (see Source) and especially the Baye
 <span class="r-in"><span><span class="op">)</span></span></span>
 <span class="r-msg co"><span class="r-pr">#&gt;</span> <span style="color: #00BBBB;">ℹ</span> For `aminoglycosides()` using columns <span style="color: #00BB00; font-weight: bold;">GEN</span> (gentamicin), <span style="color: #00BB00; font-weight: bold;">TOB</span> (tobramycin), <span style="color: #00BB00; font-weight: bold;">AMK</span></span>
 <span class="r-msg co"><span class="r-pr">#&gt;</span>   (amikacin), and <span style="color: #00BB00; font-weight: bold;">KAN</span> (kanamycin)</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># An Antibiogram: 2 × 5</span></span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># An antibiogram: 2 × 5</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># Type:           Non-WISCA with 95% CI</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>   `Grupo sindrómico` Patógeno Amikacina            Gentamicina       Tobramicina</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>              <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>                <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>             <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>      </span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span> No UCI             E. coli  100% (97-100%,N=119) 98% (96-99%,N=32… 98% (96-99…</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span> UCI                E. coli  100% (93-100%,N=52)  99% (95-100%,N=1… 96% (92-99…</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># Use `ggplot2::autoplot()` or base R `plot()` to create a plot of this antibiogram,</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># or use it directly in R Markdown or https://quarto.org, see ?antibiogram</span></span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># or use it directly in R Markdown or Quarto, see ?antibiogram</span></span>
 <span class="r-in"><span></span></span>
 <span class="r-in"><span></span></span>
 <span class="r-in"><span><span class="co"># WISCA antibiogram ----------------------------------------------------</span></span></span>
@@ -583,7 +583,7 @@ Adhering to previously described approaches (see Source) and especially the Baye
 <span class="r-in"><span>  syndromic_group <span class="op">=</span> <span class="st">"ward"</span>,</span></span>
 <span class="r-in"><span>  wisca <span class="op">=</span> <span class="cn">TRUE</span></span></span>
 <span class="r-in"><span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># An Antibiogram: 3 × 4</span></span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># An antibiogram: 3 × 4</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># Type:           WISCA with 95% CI</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>   `Syndromic Group` `Piperacillin/tazobactam` Piperacillin/tazobactam + Gentam…¹</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>             <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>                     <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>                             </span>
@@ -593,7 +593,7 @@ Adhering to previously described approaches (see Source) and especially the Baye
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ abbreviated name: ¹`Piperacillin/tazobactam + Gentamicin`</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 1 more variable: `Piperacillin/tazobactam + Tobramycin` &lt;chr&gt;</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># Use `ggplot2::autoplot()` or base R `plot()` to create a plot of this antibiogram,</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># or use it directly in R Markdown or https://quarto.org, see ?antibiogram</span></span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># or use it directly in R Markdown or Quarto, see ?antibiogram</span></span>
 <span class="r-in"><span></span></span>
 <span class="r-in"><span></span></span>
 <span class="r-in"><span><span class="co"># Print the output for R Markdown / Quarto -----------------------------</span></span></span>
--- a/reference/antibiogram.md
+++ b/reference/antibiogram.md
@@ -602,7 +602,7 @@ antibiogram(example_isolates,
 #> ℹ For `aminoglycosides()` using columns GEN (gentamicin), TOB (tobramycin), AMK
 #>   (amikacin), and KAN (kanamycin)
 #> ℹ For `carbapenems()` using columns IPM (imipenem) and MEM (meropenem)
-#> # An Antibiogram: 10 × 7
+#> # An antibiogram: 10 × 7
 #> # Type:           Non-WISCA with 95% CI
 #>    Pathogen       Amikacin    Gentamicin Imipenem Kanamycin Meropenem Tobramycin
 #>    <chr>          <chr>       <chr>      <chr>    <chr>     <chr>     <chr>     
@@ -617,7 +617,7 @@ antibiogram(example_isolates,
 #>  9 S. hominis     NA          92% (84-9… NA       NA        NA        85% (74-9…
 #> 10 S. pneumoniae  0% (0-3%,N… 0% (0-3%,… NA       0% (0-3%… NA        0% (0-3%,…
 #> # Use `ggplot2::autoplot()` or base R `plot()` to create a plot of this antibiogram,
-#> # or use it directly in R Markdown or https://quarto.org, see ?antibiogram
+#> # or use it directly in R Markdown or Quarto, see ?antibiogram

 antibiogram(example_isolates,
  antimicrobials = aminoglycosides(),
@@ -626,14 +626,14 @@ antibiogram(example_isolates,
 )
 #> ℹ For `aminoglycosides()` using columns GEN (gentamicin), TOB (tobramycin), AMK
 #>   (amikacin), and KAN (kanamycin)
-#> # An Antibiogram: 2 × 5
+#> # An antibiogram: 2 × 5
 #> # Type:           Non-WISCA with 95% CI
 #>   Pathogen      J01GB01            J01GB03             J01GB04         J01GB06  
 #>   <chr>         <chr>              <chr>               <chr>           <chr>    
 #> 1 Gram-negative 96% (94-97%,N=686) 96% (95-98%,N=684)  0% (0-10%,N=35) 98% (96-…
 #> 2 Gram-positive 34% (31-38%,N=665) 63% (60-66%,N=1170) 0% (0-1%,N=436) 0% (0-1%…
 #> # Use `ggplot2::autoplot()` or base R `plot()` to create a plot of this antibiogram,
-#> # or use it directly in R Markdown or https://quarto.org, see ?antibiogram
+#> # or use it directly in R Markdown or Quarto, see ?antibiogram

 antibiogram(example_isolates,
  antimicrobials = carbapenems(),
@@ -641,7 +641,7 @@ antibiogram(example_isolates,
  mo_transform = "name"
 )
 #> ℹ For `carbapenems()` using columns IPM (imipenem) and MEM (meropenem)
-#> # An Antibiogram: 5 × 3
+#> # An antibiogram: 5 × 3
 #> # Type:           Non-WISCA with 95% CI
 #>   Pathogen                                 Imipenem             Meropenem       
 #>   <chr>                                    <chr>                <chr>           
@@ -651,7 +651,7 @@ antibiogram(example_isolates,
 #> 4 Klebsiella pneumoniae                    100% (93-100%,N=51)  100% (93-100%,N…
 #> 5 Proteus mirabilis                        94% (79-99%,N=32)    NA              
 #> # Use `ggplot2::autoplot()` or base R `plot()` to create a plot of this antibiogram,
-#> # or use it directly in R Markdown or https://quarto.org, see ?antibiogram
+#> # or use it directly in R Markdown or Quarto, see ?antibiogram


 # Combined antibiogram -------------------------------------------------
@@ -661,7 +661,7 @@ antibiogram(example_isolates,
  antimicrobials = c("TZP", "TZP+TOB", "TZP+GEN"),
  mo_transform = "gramstain"
 )
-#> # An Antibiogram: 2 × 4
+#> # An antibiogram: 2 × 4
 #> # Type:           Non-WISCA with 95% CI
 #>   Pathogen  Piperacillin/tazobac…¹ Piperacillin/tazobac…² Piperacillin/tazobac…³
 #>   <chr>     <chr>                  <chr>                  <chr>                 
@@ -671,7 +671,7 @@ antibiogram(example_isolates,
 #> #   ²`Piperacillin/tazobactam + Gentamicin`,
 #> #   ³`Piperacillin/tazobactam + Tobramycin`
 #> # Use `ggplot2::autoplot()` or base R `plot()` to create a plot of this antibiogram,
-#> # or use it directly in R Markdown or https://quarto.org, see ?antibiogram
+#> # or use it directly in R Markdown or Quarto, see ?antibiogram

 # you can use any antimicrobial selector with `+` too:
 antibiogram(example_isolates,
@@ -679,7 +679,7 @@ antibiogram(example_isolates,
  mo_transform = "gramstain"
 )
 #> ℹ For `ureidopenicillins()` using column TZP (piperacillin/tazobactam)
-#> # An Antibiogram: 2 × 4
+#> # An antibiogram: 2 × 4
 #> # Type:           Non-WISCA with 95% CI
 #>   Pathogen  Piperacillin/tazobac…¹ Piperacillin/tazobac…² Piperacillin/tazobac…³
 #>   <chr>     <chr>                  <chr>                  <chr>                 
@@ -689,7 +689,7 @@ antibiogram(example_isolates,
 #> #   ²`Piperacillin/tazobactam + Gentamicin`,
 #> #   ³`Piperacillin/tazobactam + Tobramycin`
 #> # Use `ggplot2::autoplot()` or base R `plot()` to create a plot of this antibiogram,
-#> # or use it directly in R Markdown or https://quarto.org, see ?antibiogram
+#> # or use it directly in R Markdown or Quarto, see ?antibiogram

 # names of antimicrobials do not need to resemble columns exactly:
 antibiogram(example_isolates,
@@ -698,14 +698,14 @@ antibiogram(example_isolates,
  ab_transform = "name",
  sep = " & "
 )
-#> # An Antibiogram: 2 × 3
+#> # An antibiogram: 2 × 3
 #> # Type:           Non-WISCA with 95% CI
 #>   Pathogen      Ciprofloxacin      `Ciprofloxacin & Gentamicin`
 #>   <chr>         <chr>              <chr>                       
 #> 1 Gram-negative 91% (88-93%,N=684) 99% (97-99%,N=694)          
 #> 2 Gram-positive 77% (74-80%,N=724) 93% (91-94%,N=847)          
 #> # Use `ggplot2::autoplot()` or base R `plot()` to create a plot of this antibiogram,
-#> # or use it directly in R Markdown or https://quarto.org, see ?antibiogram
+#> # or use it directly in R Markdown or Quarto, see ?antibiogram


 # Syndromic antibiogram ------------------------------------------------
@@ -718,7 +718,7 @@ antibiogram(example_isolates,
 #> ℹ For `aminoglycosides()` using columns GEN (gentamicin), TOB (tobramycin), AMK
 #>   (amikacin), and KAN (kanamycin)
 #> ℹ For `carbapenems()` using columns IPM (imipenem) and MEM (meropenem)
-#> # An Antibiogram: 14 × 8
+#> # An antibiogram: 14 × 8
 #> # Type:           Non-WISCA with 95% CI
 #>    `Syndromic Group` Pathogen   Amikacin Gentamicin Imipenem Kanamycin Meropenem
 #>    <chr>             <chr>      <chr>    <chr>      <chr>    <chr>     <chr>    
@@ -738,7 +738,7 @@ antibiogram(example_isolates,
 #> 14 ICU               S. pneumo… 0% (0-1… 0% (0-12%… NA       0% (0-12… NA       
 #> # ℹ 1 more variable: Tobramycin <chr>
 #> # Use `ggplot2::autoplot()` or base R `plot()` to create a plot of this antibiogram,
-#> # or use it directly in R Markdown or https://quarto.org, see ?antibiogram
+#> # or use it directly in R Markdown or Quarto, see ?antibiogram

 # now define a data set with only E. coli
 ex1 <- example_isolates[which(mo_genus() == "Escherichia"), ]
@@ -756,14 +756,14 @@ antibiogram(ex1,
 )
 #> ℹ For `aminoglycosides()` using columns GEN (gentamicin), TOB (tobramycin), AMK
 #>   (amikacin), and KAN (kanamycin)
-#> # An Antibiogram: 2 × 5
+#> # An antibiogram: 2 × 5
 #> # Type:           Non-WISCA with 95% CI
 #>   `Grupo sindrómico` Patógeno Amikacina            Gentamicina       Tobramicina
 #>   <chr>              <chr>    <chr>                <chr>             <chr>      
 #> 1 No UCI             E. coli  100% (97-100%,N=119) 98% (96-99%,N=32… 98% (96-99…
 #> 2 UCI                E. coli  100% (93-100%,N=52)  99% (95-100%,N=1… 96% (92-99…
 #> # Use `ggplot2::autoplot()` or base R `plot()` to create a plot of this antibiogram,
-#> # or use it directly in R Markdown or https://quarto.org, see ?antibiogram
+#> # or use it directly in R Markdown or Quarto, see ?antibiogram


 # WISCA antibiogram ----------------------------------------------------
@@ -774,7 +774,7 @@ antibiogram(example_isolates,
  syndromic_group = "ward",
  wisca = TRUE
 )
-#> # An Antibiogram: 3 × 4
+#> # An antibiogram: 3 × 4
 #> # Type:           WISCA with 95% CI
 #>   `Syndromic Group` `Piperacillin/tazobactam` Piperacillin/tazobactam + Gentam…¹
 #>   <chr>             <chr>                     <chr>                             
@@ -784,7 +784,7 @@ antibiogram(example_isolates,
 #> # ℹ abbreviated name: ¹`Piperacillin/tazobactam + Gentamicin`
 #> # ℹ 1 more variable: `Piperacillin/tazobactam + Tobramycin` <chr>
 #> # Use `ggplot2::autoplot()` or base R `plot()` to create a plot of this antibiogram,
-#> # or use it directly in R Markdown or https://quarto.org, see ?antibiogram
+#> # or use it directly in R Markdown or Quarto, see ?antibiogram


 # Print the output for R Markdown / Quarto -----------------------------
--- a/reference/antimicrobial_selectors.html
+++ b/reference/antimicrobial_selectors.html
@@ -17,7 +17,7 @@ my_data_with_all_these_columns %&amp;gt;%

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/reference/antimicrobials.html
+++ b/reference/antimicrobials.html
@@ -9,7 +9,7 @@ The antibiotics data set has been renamed to antimicrobials. The old name will b

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/reference/as.ab.html
+++ b/reference/as.ab.html
@@ -7,7 +7,7 @@

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/reference/as.av.html
+++ b/reference/as.av.html
@@ -7,7 +7,7 @@

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/reference/as.disk.html
+++ b/reference/as.disk.html
@@ -7,7 +7,7 @@

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/reference/as.mic.html
+++ b/reference/as.mic.html
@@ -7,7 +7,7 @@

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/reference/as.mo.html
+++ b/reference/as.mo.html
@@ -7,7 +7,7 @@

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/reference/as.sir.html
+++ b/reference/as.sir.html
@@ -9,7 +9,7 @@ Breakpoints are currently implemented from EUCAST 2011-2026 and CLSI 2011-2026,

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -111,7 +111,7 @@ Breakpoints are currently implemented from EUCAST 2011-2026 and CLSI 2011-2026,
 <span>  include_PKPD <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/options.html" class="external-link">getOption</a></span><span class="op">(</span><span class="st">"AMR_include_PKPD"</span>, <span class="cn">TRUE</span><span class="op">)</span>,</span>
 <span>  breakpoint_type <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/options.html" class="external-link">getOption</a></span><span class="op">(</span><span class="st">"AMR_breakpoint_type"</span>, <span class="st">"human"</span><span class="op">)</span>, host <span class="op">=</span> <span class="cn">NULL</span>,</span>
 <span>  language <span class="op">=</span> <span class="fu"><a href="translate.html">get_AMR_locale</a></span><span class="op">(</span><span class="op">)</span>, verbose <span class="op">=</span> <span class="cn">FALSE</span>, info <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/interactive.html" class="external-link">interactive</a></span><span class="op">(</span><span class="op">)</span>,</span>
-<span>  parallel <span class="op">=</span> <span class="cn">FALSE</span>, max_cores <span class="op">=</span> <span class="op">-</span><span class="fl">1</span>, conserve_capped_values <span class="op">=</span> <span class="cn">NULL</span><span class="op">)</span></span>
+<span>  parallel <span class="op">=</span> <span class="cn">FALSE</span>, conserve_capped_values <span class="op">=</span> <span class="cn">NULL</span><span class="op">)</span></span>
 <span></span>
 <span><span class="fu">sir_interpretation_history</span><span class="op">(</span>clean <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></span></code></pre></div>
    </div>
@@ -227,11 +227,7 @@ Breakpoints are currently implemented from EUCAST 2011-2026 and CLSI 2011-2026,


 <dt id="arg-parallel">parallel<a class="anchor" aria-label="anchor" href="#arg-parallel"></a></dt>
-<dd><p>A <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate if parallel computing must be used, defaults to <code>FALSE</code>. The <code>parallel</code> package is part of base <span style="R">R</span> and no additional packages are required. On Unix/macOS with <span style="R">R</span> &gt;= 4.0.0, <code><a href="https://rdrr.io/r/parallel/mclapply.html" class="external-link">parallel::mclapply()</a></code> (fork-based) is used; on Windows and <span style="R">R</span> &lt; 4.0.0, <code><a href="https://rdrr.io/r/parallel/clusterApply.html" class="external-link">parallel::parLapply()</a></code> with a PSOCK cluster is used (requires the AMR package to be installed, not just loaded via <code>devtools::load_all()</code>). Parallelism distributes columns across cores; it is most beneficial when there are many antibiotic columns and a large number of rows.</p></dd>
-
-
-<dt id="arg-max-cores">max_cores<a class="anchor" aria-label="anchor" href="#arg-max-cores"></a></dt>
-<dd><p>Maximum number of cores to use if <code>parallel = TRUE</code>. Use a negative value to subtract that number from the available number of cores, e.g. a value of <code>-2</code> on an 8-core machine means that at most 6 cores will be used. Defaults to <code>-1</code>. There will never be used more cores than variables to analyse. The available number of cores are detected using <code><a href="https://parallelly.futureverse.org/reference/availableCores.html" class="external-link">parallelly::availableCores()</a></code> if that package is installed, and base <span style="R">R</span>'s <code><a href="https://rdrr.io/r/parallel/detectCores.html" class="external-link">parallel::detectCores()</a></code> otherwise.</p></dd>
+<dd><p>A <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate if parallel computing must be used, defaults to <code>FALSE</code>. Requires the <code><a href="https://future.apply.futureverse.org/reference/future_lapply.html" class="external-link">future.apply</a></code> package. <strong>A non-sequential <code><a href="https://future.futureverse.org/reference/plan.html" class="external-link">future::plan()</a></code> must already be active before setting <code>parallel = TRUE</code></strong> — for example, <code>future::plan(future::multisession)</code>. An error is thrown if <code>parallel = TRUE</code> is used without a plan set by the user. Parallelism distributes columns (and optionally row batches) across workers; it is most beneficial when there are many antibiotic columns and a large number of rows.</p></dd>


 <dt id="arg-clean">clean<a class="anchor" aria-label="anchor" href="#arg-clean"></a></dt>
@@ -258,7 +254,7 @@ Breakpoints are currently implemented from EUCAST 2011-2026 and CLSI 2011-2026,
 <span><span class="co"># for veterinary breakpoints, also set `host`:</span></span>
 <span><span class="va">your_data</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate_all.html" class="external-link">mutate_if</a></span><span class="op">(</span><span class="va">is.mic</span>, <span class="va">as.sir</span>, host <span class="op">=</span> <span class="st">"column_with_animal_species"</span>, guideline <span class="op">=</span> <span class="st">"CLSI"</span><span class="op">)</span></span>
 <span></span>
-<span><span class="co"># fast processing with parallel computing:</span></span>
+<span><span class="co"># fast processing with parallel computing (requires future.apply):</span></span>
 <span><span class="fu"><a href="../reference/as.sir.html">as.sir</a></span><span class="op">(</span><span class="va">your_data</span>, <span class="va">...</span>, parallel <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></code></pre><p></p></div></li>
 <li><p>Operators like "&lt;=" will be considered according to the <code>capped_mic_handling</code> setting. At default, an MIC value of e.g. "&gt;2" will return "NI" (non-interpretable) if the breakpoint is 4-8; the <em>true</em> MIC could be at either side of the breakpoint. This is to prevent that capped values from raw laboratory data would not be treated conservatively.</p></li>
 <li><p><strong>Note:</strong> When using CLSI as the guideline, MIC values must be log2-based doubling dilutions. Values not in this format, will be automatically rounded up to the nearest log2 level as CLSI instructs, and a warning will be thrown.</p></li>
@@ -272,7 +268,7 @@ Breakpoints are currently implemented from EUCAST 2011-2026 and CLSI 2011-2026,
 <span><span class="co"># for veterinary breakpoints, also set `host`:</span></span>
 <span><span class="va">your_data</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate_all.html" class="external-link">mutate_if</a></span><span class="op">(</span><span class="va">is.disk</span>, <span class="va">as.sir</span>, host <span class="op">=</span> <span class="st">"column_with_animal_species"</span>, guideline <span class="op">=</span> <span class="st">"CLSI"</span><span class="op">)</span></span>
 <span></span>
-<span><span class="co"># fast processing with parallel computing:</span></span>
+<span><span class="co"># fast processing with parallel computing (requires future.apply):</span></span>
 <span><span class="fu"><a href="../reference/as.sir.html">as.sir</a></span><span class="op">(</span><span class="va">your_data</span>, <span class="va">...</span>, parallel <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></code></pre><p></p></div></li>
 </ul></li>
 <li><p>For <strong>interpreting a complete data set</strong>, with automatic determination of MIC values, disk diffusion diameters, microorganism names or codes, and antimicrobial test results. This is done very simply by running <code>as.sir(your_data)</code>.</p></li>
@@ -424,29 +420,15 @@ Breakpoints are currently implemented from EUCAST 2011-2026 and CLSI 2011-2026,
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 4 × 18</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>   datetime            index method ab_given    mo_given   host_given input_given</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;dttm&gt;</span>              <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>  <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>       <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>      <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>      <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>      </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span> 2026-04-25 <span style="color: #949494;">14:25:30</span>     1 MIC    amoxicillin Escherich… human      8          </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span> 2026-04-25 <span style="color: #949494;">14:25:30</span>     1 MIC    cipro       Escherich… human      0.256      </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span> 2026-04-25 <span style="color: #949494;">14:25:31</span>     1 DISK   tobra       Escherich… human      16         </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">4</span> 2026-04-25 <span style="color: #949494;">14:25:31</span>     1 DISK   genta       Escherich… human      18         </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span> 2026-04-30 <span style="color: #949494;">08:03:38</span>     1 MIC    amoxicillin Escherich… human      8          </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span> 2026-04-30 <span style="color: #949494;">08:03:38</span>     1 MIC    cipro       Escherich… human      0.256      </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span> 2026-04-30 <span style="color: #949494;">08:03:38</span>     1 DISK   tobra       Escherich… human      16         </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">4</span> 2026-04-30 <span style="color: #949494;">08:03:39</span>     1 DISK   genta       Escherich… human      18         </span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 11 more variables: ab &lt;ab&gt;, mo &lt;mo&gt;, host &lt;chr&gt;, input &lt;chr&gt;,</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;">#   outcome &lt;sir&gt;, notes &lt;chr&gt;, guideline &lt;chr&gt;, ref_table &lt;chr&gt;, uti &lt;lgl&gt;,</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;">#   breakpoint_S_R &lt;chr&gt;, site &lt;chr&gt;</span></span>
 <span class="r-in"><span></span></span>
 <span class="r-in"><span><span class="co"># \donttest{</span></span></span>
-<span class="r-in"><span><span class="co"># using parallel computing, which is available in base R:</span></span></span>
-<span class="r-in"><span><span class="fu">as.sir</span><span class="op">(</span><span class="va">df_wide</span>, parallel <span class="op">=</span> <span class="cn">TRUE</span>, info <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span>
-<span class="r-msg co"><span class="r-pr">#&gt;</span> <span style="color: #00BBBB;">ℹ</span> Run `sir_interpretation_history()` afterwards to retrieve a logbook with all</span>
-<span class="r-msg co"><span class="r-pr">#&gt;</span>   details of the breakpoint interpretations.</span>
-<span class="r-msg co"><span class="r-pr">#&gt;</span> </span>
-<span class="r-msg co"><span class="r-pr">#&gt;</span> Processing columns:</span>
-<span class="r-msg co"><span class="r-pr">#&gt;</span> </span>
-<span class="r-msg co"><span class="r-pr">#&gt;</span> <span style="color: #080808; background-color: #5FD7AF;"> DONE </span></span>
-<span class="r-msg co"><span class="r-pr">#&gt;</span> </span>
-<span class="r-msg co"><span class="r-pr">#&gt;</span> <span style="color: #00BBBB;">ℹ</span> Run `sir_interpretation_history()` to retrieve a logbook with all details of</span>
-<span class="r-msg co"><span class="r-pr">#&gt;</span>   the breakpoint interpretations.</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>      microorganism amoxicillin cipro tobra genta ERY</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 1 Escherichia coli           S     I     S     S   R</span>
-<span class="r-in"><span></span></span>
 <span class="r-in"><span></span></span>
 <span class="r-in"><span><span class="co">## Using dplyr -------------------------------------------------</span></span></span>
 <span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://dplyr.tidyverse.org" class="external-link">"dplyr"</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span></span></span>
--- a/reference/as.sir.md
+++ b/reference/as.sir.md
@@ -69,7 +69,7 @@ as.sir(x, ..., col_mo = NULL,
  include_PKPD = getOption("AMR_include_PKPD", TRUE),
  breakpoint_type = getOption("AMR_breakpoint_type", "human"), host = NULL,
  language = get_AMR_locale(), verbose = FALSE, info = interactive(),
-  parallel = FALSE, max_cores = -1, conserve_capped_values = NULL)
+  parallel = FALSE, conserve_capped_values = NULL)

 sir_interpretation_history(clean = FALSE)
 ```
@@ -348,28 +348,16 @@ disk diffusion diameters:
 - parallel:

  A [logical](https://rdrr.io/r/base/logical.html) to indicate if
-  parallel computing must be used, defaults to `FALSE`. The `parallel`
-  package is part of base R and no additional packages are required. On
-  Unix/macOS with R \>= 4.0.0,
-  [`parallel::mclapply()`](https://rdrr.io/r/parallel/mclapply.html)
-  (fork-based) is used; on Windows and R \< 4.0.0,
-  [`parallel::parLapply()`](https://rdrr.io/r/parallel/clusterApply.html)
-  with a PSOCK cluster is used (requires the AMR package to be
-  installed, not just loaded via `devtools::load_all()`). Parallelism
-  distributes columns across cores; it is most beneficial when there are
-  many antibiotic columns and a large number of rows.
-
- max_cores:
-
-  Maximum number of cores to use if `parallel = TRUE`. Use a negative
-  value to subtract that number from the available number of cores, e.g.
-  a value of `-2` on an 8-core machine means that at most 6 cores will
-  be used. Defaults to `-1`. There will never be used more cores than
-  variables to analyse. The available number of cores are detected using
-  [`parallelly::availableCores()`](https://parallelly.futureverse.org/reference/availableCores.html)
-  if that package is installed, and base R's
-  [`parallel::detectCores()`](https://rdrr.io/r/parallel/detectCores.html)
-  otherwise.
+  parallel computing must be used, defaults to `FALSE`. Requires the
+  [`future.apply`](https://future.apply.futureverse.org/reference/future_lapply.html)
+  package. **A non-sequential
+  [`future::plan()`](https://future.futureverse.org/reference/plan.html)
+  must already be active before setting `parallel = TRUE`** — for
+  example, `future::plan(future::multisession)`. An error is thrown if
+  `parallel = TRUE` is used without a plan set by the user. Parallelism
+  distributes columns (and optionally row batches) across workers; it is
+  most beneficial when there are many antibiotic columns and a large
+  number of rows.

 - clean:

@@ -425,7 +413,7 @@ The `as.sir()` function can work in four ways:
          # for veterinary breakpoints, also set `host`:
          your_data %>% mutate_if(is.mic, as.sir, host = "column_with_animal_species", guideline = "CLSI")

-          # fast processing with parallel computing:
+          # fast processing with parallel computing (requires future.apply):
          as.sir(your_data, ..., parallel = TRUE)

    - Operators like "\<=" will be considered according to the
@@ -458,7 +446,7 @@ The `as.sir()` function can work in four ways:
          # for veterinary breakpoints, also set `host`:
          your_data %>% mutate_if(is.disk, as.sir, host = "column_with_animal_species", guideline = "CLSI")

-          # fast processing with parallel computing:
+          # fast processing with parallel computing (requires future.apply):
          as.sir(your_data, ..., parallel = TRUE)

 4.  For **interpreting a complete data set**, with automatic
@@ -679,29 +667,15 @@ sir_interpretation_history()
 #> # A tibble: 4 × 18
 #>   datetime            index method ab_given    mo_given   host_given input_given
 #>   <dttm>              <int> <chr>  <chr>       <chr>      <chr>      <chr>      
-#> 1 2026-04-25 14:25:30     1 MIC    amoxicillin Escherich… human      8          
-#> 2 2026-04-25 14:25:30     1 MIC    cipro       Escherich… human      0.256      
-#> 3 2026-04-25 14:25:31     1 DISK   tobra       Escherich… human      16         
-#> 4 2026-04-25 14:25:31     1 DISK   genta       Escherich… human      18         
+#> 1 2026-04-30 08:03:38     1 MIC    amoxicillin Escherich… human      8          
+#> 2 2026-04-30 08:03:38     1 MIC    cipro       Escherich… human      0.256      
+#> 3 2026-04-30 08:03:38     1 DISK   tobra       Escherich… human      16         
+#> 4 2026-04-30 08:03:39     1 DISK   genta       Escherich… human      18         
 #> # ℹ 11 more variables: ab <ab>, mo <mo>, host <chr>, input <chr>,
 #> #   outcome <sir>, notes <chr>, guideline <chr>, ref_table <chr>, uti <lgl>,
 #> #   breakpoint_S_R <chr>, site <chr>

 # \donttest{
-# using parallel computing, which is available in base R:
-as.sir(df_wide, parallel = TRUE, info = TRUE)
-#> ℹ Run `sir_interpretation_history()` afterwards to retrieve a logbook with all
-#>   details of the breakpoint interpretations.
-#> 
-#> Processing columns:
-#> 
-#>  DONE 
-#> 
-#> ℹ Run `sir_interpretation_history()` to retrieve a logbook with all details of
-#>   the breakpoint interpretations.
-#>      microorganism amoxicillin cipro tobra genta ERY
-#> 1 Escherichia coli           S     I     S     S   R
-

 ## Using dplyr -------------------------------------------------
 if (require("dplyr")) {
--- a/reference/atc_online.html
+++ b/reference/atc_online.html
@@ -7,7 +7,7 @@

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/reference/av_from_text.html
+++ b/reference/av_from_text.html
@@ -7,7 +7,7 @@

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/reference/av_property.html
+++ b/reference/av_property.html
@@ -7,7 +7,7 @@

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/reference/availability.html
+++ b/reference/availability.html
@@ -7,7 +7,7 @@

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/reference/bug_drug_combinations.html
+++ b/reference/bug_drug_combinations.html
@@ -7,7 +7,7 @@

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/reference/clinical_breakpoints.html
+++ b/reference/clinical_breakpoints.html
@@ -21,7 +21,7 @@ Use as.sir() to transform MICs or disks measurements to SIR values."><meta prope

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/reference/count.html
+++ b/reference/count.html
@@ -9,7 +9,7 @@ count_resistant() should be used to count resistant isolates, count_susceptible(

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/reference/custom_eucast_rules.html
+++ b/reference/custom_eucast_rules.html
@@ -7,7 +7,7 @@

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/reference/custom_mdro_guideline.html
+++ b/reference/custom_mdro_guideline.html
@@ -7,7 +7,7 @@

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/reference/dosage.html
+++ b/reference/dosage.html
@@ -7,7 +7,7 @@

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/reference/esbl_isolates.html
+++ b/reference/esbl_isolates.html
@@ -7,7 +7,7 @@

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/reference/example_isolates.html
+++ b/reference/example_isolates.html
@@ -7,7 +7,7 @@

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/reference/example_isolates_unclean.html
+++ b/reference/example_isolates_unclean.html
@@ -7,7 +7,7 @@

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/reference/export_ncbi_biosample.html
+++ b/reference/export_ncbi_biosample.html
@@ -7,7 +7,7 @@

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/reference/first_isolate.html
+++ b/reference/first_isolate.html
@@ -9,7 +9,7 @@

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/reference/first_isolate.md
+++ b/reference/first_isolate.md
@@ -210,7 +210,7 @@ subspecies).
 All mentioned methods are covered in the `first_isolate()` function:

 |  |  |
-|-------------------------------------------------|--------------------------------------------------------|
+|----|----|
 | **Method** | **Function to apply** |
 | **Isolate-based** | `first_isolate(x, method = "isolate-based")` |
 | *(= all isolates)* |  |
--- a/reference/g.test.html
+++ b/reference/g.test.html
@@ -7,7 +7,7 @@

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/reference/get_episode.html
+++ b/reference/get_episode.html
@@ -7,7 +7,7 @@

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/reference/ggplot_pca.html
+++ b/reference/ggplot_pca.html
@@ -7,7 +7,7 @@

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/reference/ggplot_sir.html
+++ b/reference/ggplot_sir.html
@@ -7,7 +7,7 @@

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/reference/guess_ab_col.html
+++ b/reference/guess_ab_col.html
@@ -7,7 +7,7 @@

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/reference/index.html
+++ b/reference/index.html
@@ -7,7 +7,7 @@

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/reference/interpretive_rules.html
+++ b/reference/interpretive_rules.html
@@ -9,7 +9,7 @@ To improve the interpretation of the antibiogram before CLSI/EUCAST interpretive

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/reference/intrinsic_resistant.html
+++ b/reference/intrinsic_resistant.html
@@ -7,7 +7,7 @@

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/reference/italicise_taxonomy.html
+++ b/reference/italicise_taxonomy.html
@@ -7,7 +7,7 @@

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/reference/join.html
+++ b/reference/join.html
@@ -7,7 +7,7 @@

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/reference/key_antimicrobials.html
+++ b/reference/key_antimicrobials.html
@@ -7,7 +7,7 @@

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/reference/kurtosis.html
+++ b/reference/kurtosis.html
@@ -7,7 +7,7 @@

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/reference/like.html
+++ b/reference/like.html
@@ -7,7 +7,7 @@

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/reference/mdro.html
+++ b/reference/mdro.html
@@ -7,7 +7,7 @@

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/reference/mean_amr_distance.html
+++ b/reference/mean_amr_distance.html
@@ -7,7 +7,7 @@

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/reference/microorganisms.codes.html
+++ b/reference/microorganisms.codes.html
@@ -7,7 +7,7 @@

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/reference/microorganisms.groups.html
+++ b/reference/microorganisms.groups.html
@@ -7,7 +7,7 @@

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/reference/microorganisms.html
+++ b/reference/microorganisms.html
@@ -9,7 +9,7 @@ This data set is carefully crafted, yet made 100% reproducible from public and a

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/reference/mo_matching_score.html
+++ b/reference/mo_matching_score.html
@@ -7,7 +7,7 @@

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/reference/mo_property.html
+++ b/reference/mo_property.html
@@ -7,7 +7,7 @@

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/reference/mo_source.html
+++ b/reference/mo_source.html
@@ -9,7 +9,7 @@ This is the fastest way to have your organisation (or analysis) specific codes p

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/reference/pca.html
+++ b/reference/pca.html
@@ -7,7 +7,7 @@

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/reference/plot.html
+++ b/reference/plot.html
@@ -9,7 +9,7 @@ Especially the scale_*_mic() functions are relevant wrappers to plot MIC values

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/reference/proportion.html
+++ b/reference/proportion.html
@@ -9,7 +9,7 @@ resistance() should be used to calculate resistance, susceptibility() should be

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/reference/random.html
+++ b/reference/random.html
@@ -7,7 +7,7 @@

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/reference/resistance_predict.html
+++ b/reference/resistance_predict.html
@@ -9,7 +9,7 @@ NOTE: These functions are deprecated and will be removed in a future version. Us

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/reference/skewness.html
+++ b/reference/skewness.html
@@ -9,7 +9,7 @@ When negative ('left-skewed'): the left tail is longer; the mass of the distribu

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/reference/top_n_microorganisms.html
+++ b/reference/top_n_microorganisms.html
@@ -7,7 +7,7 @@

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/reference/translate.html
+++ b/reference/translate.html
@@ -7,7 +7,7 @@

    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>

-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9052</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9053</small>


    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
--- a/search.json
+++ b/search.json