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<title>Welcome to the `AMR` package • AMR (for R)</title>
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<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9259</small>
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<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9263</small>
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@@ -91,89 +90,83 @@
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<p>Note: to keep the package size as small as possible, we only include
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this vignette on CRAN. You can read more vignettes on our website about
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how to conduct AMR data analysis, determine MDROs, find explanation of
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EUCAST and CLSI breakpoints, and much more: <a href="https://amr-for-r.org/articles/" class="uri">https://amr-for-r.org/articles/</a>.</p>
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EUCAST and CLSI breakpoints, and much more: <a href="https://amr-for-r.org" class="uri">https://amr-for-r.org</a>.</p>
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<hr>
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<p>The <code>AMR</code> package is a <a href="https://amr-for-r.org/">free and open-source</a> R package with <a href="https://en.wikipedia.org/wiki/Dependency_hell" class="external-link">zero
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<p>The <code>AMR</code> package is a peer-reviewed, <a href="https://amr-for-r.org/#copyright">free and open-source</a> R
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package with <a href="https://en.wikipedia.org/wiki/Dependency_hell" class="external-link">zero
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dependencies</a> to simplify the analysis and prediction of
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Antimicrobial Resistance (AMR) and to work with microbial and
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antimicrobial data and properties, by using evidence-based methods.
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<strong>Our aim is to provide a standard</strong> for clean and
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reproducible AMR data analysis, that can therefore empower
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epidemiological analyses to continuously enable surveillance and
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treatment evaluation in any setting. <a href="https://amr-for-r.org/authors.html">Many different researchers</a>
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from around the globe are continually helping us to make this a
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successful and durable project!</p>
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treatment evaluation in any setting. We are a team of <a href="https://amr-for-r.org/authors.html">many different researchers</a>
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from around the globe to make this a successful and durable project!</p>
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<p>This work was published in the Journal of Statistical Software
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(Volume 104(3); <a href="https://doi.org/10.18637/jss.v104.i03" class="external-link">DOI
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10.18637/jss.v104.i03</a>) and formed the basis of two PhD theses (<a href="https://doi.org/10.33612/diss.177417131" class="external-link">DOI
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10.33612/diss.177417131</a> and <a href="https://doi.org/10.33612/diss.192486375" class="external-link">DOI
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10.33612/diss.192486375</a>).</p>
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<p>After installing this package, R knows ~79 000 distinct microbial
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species and all ~620 antibiotic, antimycotic and antiviral drugs by name
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and code (including ATC, EARS-Net, ASIARS-Net, PubChem, LOINC and SNOMED
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CT), and knows all about valid SIR and MIC values. The integral
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breakpoint guidelines from CLSI and EUCAST are included from the last 10
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years. It supports and can read any data format, including WHONET
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data.</p>
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<p>With the help of contributors from all corners of the world, the
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<code>AMR</code> package is available in English, Czech, Chinese,
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(Volume 104(3); ) and formed the basis of two PhD theses ( and ).</p>
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<p>After installing this package, R knows <a href="https://amr-for-r.org/reference/microorganisms.html"><strong>~79
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000 distinct microbial species</strong></a> (updated June 2024) and all
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<a href="https://amr-for-r.org/reference/antimicrobials.html"><strong>~620
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antimicrobial and antiviral drugs</strong></a> by name and code
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(including ATC, EARS-Net, ASIARS-Net, PubChem, LOINC and SNOMED CT), and
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knows all about valid SIR and MIC values. The integral clinical
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breakpoint guidelines from CLSI 2011-2025 and EUCAST 2011-2025 are
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included, even with epidemiological cut-off (ECOFF) values. It supports
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and can read any data format, including WHONET data. This package works
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on Windows, macOS and Linux with all versions of R since R-3.0 (April
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2013). <strong>It was designed to work in any setting, including those
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with very limited resources</strong>. It was created for both routine
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data analysis and academic research at the Faculty of Medical Sciences
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of the <a href="https://www.rug.nl" class="external-link">University of Groningen</a> and the
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<a href="https://www.umcg.nl" class="external-link">University Medical Center
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Groningen</a>.</p>
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<p>The <code>AMR</code> package is available in English, Chinese, Czech,
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Danish, Dutch, Finnish, French, German, Greek, Italian, Japanese,
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Norwegian, Polish, Portuguese, Romanian, Russian, Spanish, Swedish,
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Turkish, and Ukrainian. Antimicrobial drug (group) names and colloquial
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microorganism names are provided in these languages.</p>
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<p>This package is fully independent of any other R package and works on
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Windows, macOS and Linux with all versions of R since R-3.0 (April
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2013). <strong>It was designed to work in any setting, including those
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with very limited resources</strong>. Since its first public release in
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early 2018, this package has been downloaded from more than 175
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countries.</p>
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<p>This package can be used for:</p>
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<p>This package was intended as a comprehensive toolbox for integrated
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AMR data analysis. This package can be used for:</p>
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<ul>
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<li>Reference for the taxonomy of microorganisms, since the package
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contains all microbial (sub)species from the List of Prokaryotic names
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with Standing in Nomenclature (LPSN) and the Global Biodiversity
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Information Facility (GBIF)</li>
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<li>Interpreting raw MIC and disk diffusion values, based on the latest
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CLSI or EUCAST guidelines</li>
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with Standing in Nomenclature (<a href="(https://lpsn.dsmz.de)" class="external-link">LPSN</a>) and the Global Biodiversity
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Information Facility (<a href="https://www.gbif.org" class="external-link">GBIF</a>) (<a href="https://amr-for-r.org/reference/mo_property.html">manual</a>)</li>
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<li>Interpreting raw MIC and disk diffusion values, based on any CLSI or
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EUCAST guideline (<a href="https://amr-for-r.org/reference/as.sir.html">manual</a>)</li>
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<li>Retrieving antimicrobial drug names, doses and forms of
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administration from clinical health care records</li>
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<li>Determining first isolates to be used for AMR data analysis</li>
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<li>Calculating antimicrobial resistance</li>
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administration from clinical health care records (<a href="https://amr-for-r.org/reference/ab_from_text.html">manual</a>)</li>
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<li>Determining first isolates to be used for AMR data analysis (<a href="https://amr-for-r.org/reference/first_isolate.html">manual</a>)</li>
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<li>Calculating antimicrobial resistance (<a href="https://amr-for-r.org/articles/AMR.html">tutorial</a>)</li>
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<li>Determining multi-drug resistance (MDR) / multi-drug resistant
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organisms (MDRO)</li>
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organisms (MDRO) (<a href="https://amr-for-r.org/articles/MDR.html">tutorial</a>)</li>
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<li>Calculating (empirical) susceptibility of both mono therapy and
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combination therapies</li>
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<li>Predicting future antimicrobial resistance using regression
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models</li>
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combination therapies (<a href="https://amr-for-r.org/articles/AMR.html">tutorial</a>)</li>
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<li>Apply AMR function in predictive modelling (<a href="https://amr-for-r.org/articles/AMR_with_tidymodels.html">tutorial</a>)</li>
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<li>Getting properties for any microorganism (like Gram stain, species,
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genus or family)</li>
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<li>Getting properties for any antibiotic (like name, code of
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EARS-Net/ATC/LOINC/PubChem, defined daily dose or trade name)</li>
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<li>Plotting antimicrobial resistance</li>
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<li>Applying EUCAST expert rules</li>
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genus or family) (<a href="https://amr-for-r.org/reference/mo_property.html">manual</a>)</li>
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<li>Getting properties for any antimicrobial (like name, code of
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EARS-Net/ATC/LOINC/PubChem, defined daily dose or trade name) (<a href="https://amr-for-r.org/reference/ab_property.html">manual</a>)</li>
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<li>Plotting antimicrobial resistance (<a href="https://amr-for-r.org/articles/AMR.html">tutorial</a>)</li>
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<li>Applying EUCAST expert rules (<a href="https://amr-for-r.org/reference/eucast_rules.html">manual</a>)</li>
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<li>Getting SNOMED codes of a microorganism, or getting properties of a
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microorganism based on a SNOMED code</li>
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microorganism based on a SNOMED code (<a href="https://amr-for-r.org/reference/mo_property.html">manual</a>)</li>
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<li>Getting LOINC codes of an antibiotic, or getting properties of an
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antibiotic based on a LOINC code</li>
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<li>Machine reading the EUCAST and CLSI guidelines from 2011-2020 to
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translate MIC values and disk diffusion diameters to SIR</li>
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<li>Principal component analysis for AMR</li>
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antibiotic based on a LOINC code (<a href="https://amr-for-r.org/reference/ab_property.html">manual</a>)</li>
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<li>Machine reading the EUCAST and CLSI guidelines from 2011-2021 to
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translate MIC values and disk diffusion diameters to SIR (<a href="https://amr-for-r.org/articles/datasets.html">link</a>)</li>
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<li>Principal component analysis for AMR (<a href="https://amr-for-r.org/articles/PCA.html">tutorial</a>)</li>
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</ul>
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<p>All reference data sets (about microorganisms, antimicrobials, SIR
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interpretation, EUCAST rules, etc.) in this <code>AMR</code> package are
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publicly and freely available. We continually export our data sets to
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formats for use in R, SPSS, Stata and Excel. We also supply flat files
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that are machine-readable and suitable for input in any software
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program, such as laboratory information systems. Please find <a href="https://amr-for-r.org/articles/datasets.html">all download links
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on our website</a>, which is automatically updated with every code
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change.</p>
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<p>This R package was created for both routine data analysis and
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academic research at the Faculty of Medical Sciences of the <a href="https://www.rug.nl" class="external-link">University of Groningen</a>, in collaboration
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with non-profit organisations <a href="https://www.certe.nl" class="external-link">Certe
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Medical Diagnostics and Advice Foundation</a> and <a href="https://www.umcg.nl" class="external-link">University Medical Center Groningen</a>, and
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is being <a href="https://amr-for-r.org/news/">actively and durably
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maintained</a> by two public healthcare organisations in the
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Netherlands.</p>
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<p>All reference data sets in the AMR package - including information on
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microorganisms, antimicrobials, and clinical breakpoints - are freely
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available for download in multiple formats: R, MS Excel, Apache Feather,
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Apache Parquet, SPSS, and Stata.</p>
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<p>For maximum compatibility, we also provide machine-readable,
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tab-separated plain text files suitable for use in any software,
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including laboratory information systems.</p>
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<p>Visit <a href="https://amr-for-r.org/articles/datasets.html">our
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website for direct download links</a>, or explore the actual files in <a href="https://github.com/msberends/AMR/tree/main/data-raw/datasets" class="external-link">our
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GitHub repository</a>.</p>
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<hr>
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<p><small> This AMR package for R is free, open-source software and
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licensed under the <a href="https://amr-for-r.org/LICENSE-text.html">GNU
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