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(v1.3.0.9033) skimr fix
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@ -82,7 +82,7 @@
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</button>
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<span class="navbar-brand">
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<a class="navbar-link" href="../index.html">AMR (for R)</a>
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<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.3.0.9032</span>
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<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.3.0.9033</span>
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</span>
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</div>
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@ -388,7 +388,7 @@ The <a href='lifecycle.html'>lifecycle</a> of this function is <strong>stable</s
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<p>With ambiguous user input in <code>as.mo()</code> and all the <code><a href='mo_property.html'>mo_*</a></code> functions, the returned results are chosen based on their matching score using <code><a href='mo_matching_score.html'>mo_matching_score()</a></code>. This matching score \(m\), ranging from 0 to 100%, is calculated as:</p>
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<p>With ambiguous user input in <code>as.mo()</code> and all the <code><a href='mo_property.html'>mo_*</a></code> functions, the returned results are chosen based on their matching score using <code><a href='mo_matching_score.html'>mo_matching_score()</a></code>. This matching score \(m\), is calculated as:</p>
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<p>$$m_{(x, n)} = \frac{l_{n} - 0.5 \cdot \min \begin{cases}l_{n} \\ \operatorname{lev}(x, n)\end{cases}}{l_{n} \cdot p_{n} \cdot k_{n}}$$</p>
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<p>where:</p><ul>
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<li><p>\(x\) is the user input;</p></li>
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@ -83,7 +83,7 @@ To improve the interpretation of the antibiogram before EUCAST rules are applied
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</button>
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<span class="navbar-brand">
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<a class="navbar-link" href="../index.html">AMR (for R)</a>
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<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.3.0.9028</span>
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<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.3.0.9033</span>
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</span>
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</div>
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@ -280,11 +280,11 @@ To improve the interpretation of the antibiogram before EUCAST rules are applied
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</tr>
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<tr>
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<th>version_breakpoints</th>
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<td><p>the version number to use for the EUCAST Clinical Breakpoints guideline</p></td>
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<td><p>the version number to use for the EUCAST Clinical Breakpoints guideline. Currently supported: 10.0.</p></td>
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</tr>
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<tr>
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<th>version_expertrules</th>
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<td><p>the version number to use for the EUCAST Expert Rules and Intrinsic Resistance guideline</p></td>
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<td><p>the version number to use for the EUCAST Expert Rules and Intrinsic Resistance guideline. Currently supported: 3.1, 3.2.</p></td>
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</tr>
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<tr>
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<th>...</th>
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@ -81,7 +81,7 @@
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</button>
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<span class="navbar-brand">
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<a class="navbar-link" href="../index.html">AMR (for R)</a>
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<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.3.0.9032</span>
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<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.3.0.9033</span>
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</span>
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</div>
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@ -82,7 +82,7 @@
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</button>
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<span class="navbar-brand">
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<a class="navbar-link" href="../index.html">AMR (for R)</a>
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<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.3.0.9032</span>
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<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.3.0.9033</span>
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</span>
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</div>
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@ -261,7 +261,7 @@
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<p>With ambiguous user input in <code><a href='as.mo.html'>as.mo()</a></code> and all the <code><a href='mo_property.html'>mo_*</a></code> functions, the returned results are chosen based on their matching score using <code>mo_matching_score()</code>. This matching score \(m\), ranging from 0 to 100%, is calculated as:</p>
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<p>With ambiguous user input in <code><a href='as.mo.html'>as.mo()</a></code> and all the <code><a href='mo_property.html'>mo_*</a></code> functions, the returned results are chosen based on their matching score using <code>mo_matching_score()</code>. This matching score \(m\), is calculated as:</p>
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<p>$$m_{(x, n)} = \frac{l_{n} - 0.5 \cdot \min \begin{cases}l_{n} \\ \operatorname{lev}(x, n)\end{cases}}{l_{n} \cdot p_{n} \cdot k_{n}}$$</p>
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<p>where:</p><ul>
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<li><p>\(x\) is the user input;</p></li>
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@ -82,7 +82,7 @@
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</button>
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<span class="navbar-brand">
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<a class="navbar-link" href="../index.html">AMR (for R)</a>
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<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.3.0.9032</span>
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<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.3.0.9033</span>
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</span>
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</div>
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@ -350,7 +350,7 @@ The <a href='lifecycle.html'>lifecycle</a> of this function is <strong>stable</s
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<p>With ambiguous user input in <code><a href='as.mo.html'>as.mo()</a></code> and all the <code>mo_*</code> functions, the returned results are chosen based on their matching score using <code><a href='mo_matching_score.html'>mo_matching_score()</a></code>. This matching score \(m\), ranging from 0 to 100%, is calculated as:</p>
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<p>With ambiguous user input in <code><a href='as.mo.html'>as.mo()</a></code> and all the <code>mo_*</code> functions, the returned results are chosen based on their matching score using <code><a href='mo_matching_score.html'>mo_matching_score()</a></code>. This matching score \(m\), is calculated as:</p>
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<p>$$m_{(x, n)} = \frac{l_{n} - 0.5 \cdot \min \begin{cases}l_{n} \\ \operatorname{lev}(x, n)\end{cases}}{l_{n} \cdot p_{n} \cdot k_{n}}$$</p>
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<p>where:</p><ul>
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<li><p>\(x\) is the user input;</p></li>
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