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.nojekyll

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evaluation/badges.html

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<p><em>Caveat: Please note that these criteria are based on available information about each badge online, and that we have likely differences in our procedure (e.g.&nbsp;allowed troubleshooting for execution and reproduction, not under tight time pressure to complete). Moreover, we focus only on reproduction of the discrete-event simulation, and not on other aspects of the article. We cannot guarantee that the badges below would have been awarded in practice by these journals.</em></p>
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<section id="criteria" class="level2">
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<h2 class="anchored" data-anchor-id="criteria">Criteria</h2>
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<details class="code-fold">
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<summary>Code</summary>
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<div class="sourceCode cell-code" id="cb1"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb1-1"><a href="#cb1-1" aria-hidden="true" tabindex="-1"></a><span class="im">from</span> IPython.display <span class="im">import</span> display, Markdown</span>
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<h2 class="anchored" data-anchor-id="badges">Badges</h2>
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<summary>Code</summary>
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<div class="sourceCode cell-code" id="cb2"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb2-1"><a href="#cb2-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Full badge names</span></span>

evaluation/logbook.html

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<div class="quarto-post image-right" data-index="0" data-categories="guidelines" data-listing-date-sort="1717545600000" data-listing-file-modified-sort="1717756856730" data-listing-date-modified-sort="NaN" data-listing-reading-time-sort="8" data-listing-word-count-sort="1439">
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<div class="listing-item-img-placeholder card-img-top" >&nbsp;</div>
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<p><a href="../evaluation/posts/2024_06_04/index.html" class="no-external"></a></p><a href="../evaluation/posts/2024_06_04/index.html" class="no-external">
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<div class="quarto-post image-right" data-index="2" data-categories="reproduce" data-listing-date-sort="1717372800000" data-listing-file-modified-sort="1717755016374" data-listing-date-modified-sort="NaN" data-listing-reading-time-sort="5" data-listing-word-count-sort="879">
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<div class="quarto-post image-right" data-index="2" data-categories="reproduce" data-listing-date-sort="1717372800000" data-listing-file-modified-sort="1717756856730" data-listing-date-modified-sort="NaN" data-listing-reading-time-sort="5" data-listing-word-count-sort="879">
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<p><a href="../evaluation/posts/2024_06_03/index.html" class="no-external"></a></p><a href="../evaluation/posts/2024_06_03/index.html" class="no-external">
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<p class="card-img-top"><img src="../original_study/article_fig2.png" class="thumbnail-image card-img"/></p>
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<p class="card-img-top"><img src="posts/2024_05_24/figure_1a.png" class="thumbnail-image card-img"/></p>
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<p class="card-img-top"><img src="../original_study/article_fig4.png" class="thumbnail-image card-img"/></p>
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<div class="quarto-post image-right" data-index="5" data-categories="setup,read,scope" data-listing-date-sort="1716336000000" data-listing-file-modified-sort="1717756856722" data-listing-date-modified-sort="NaN" data-listing-reading-time-sort="9" data-listing-word-count-sort="1786">
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<p class="card-img-top"><img src="../original_study/article_fig1.png" class="thumbnail-image card-img"/></p>

evaluation/posts/2024_05_22/index.html

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<section id="timings" class="level2">
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<h2 class="anchored" data-anchor-id="timings">Timings</h2>
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<div id="fd800a25" class="cell" data-execution_count="1">
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<div class="sourceCode cell-code" id="cb1"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb1-1"><a href="#cb1-1" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> sys</span>
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<span id="cb1-2"><a href="#cb1-2" aria-hidden="true" tabindex="-1"></a>sys.path.append(<span class="st">'../'</span>)</span>
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<span id="cb1-3"><a href="#cb1-3" aria-hidden="true" tabindex="-1"></a><span class="im">from</span> timings <span class="im">import</span> calculate_times</span>

evaluation/posts/2024_05_23/index.html

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<h2 class="anchored" data-anchor-id="timings">Timings</h2>
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<div class="sourceCode cell-code" id="cb5"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb5-1"><a href="#cb5-1" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> sys</span>
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<span id="cb5-2"><a href="#cb5-2" aria-hidden="true" tabindex="-1"></a>sys.path.append(<span class="st">'../'</span>)</span>
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<span id="cb5-3"><a href="#cb5-3" aria-hidden="true" tabindex="-1"></a><span class="im">from</span> timings <span class="im">import</span> calculate_times</span>

evaluation/posts/2024_05_24/index.html

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<p>Exploring methods for overlaying figures. Not timed as not about reproduction of this study, but about how we are going to do this each time when reproducing.</p>
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<p>Decided that it’s not helpful to do this - spend more time fiddling around with getting them to resize and overlay correctly - and that the simplest option here would be to compare by eye.</p>
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<p>If timed, 13.33-13.57.</p>
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<div id="bb38e7e6" class="cell" data-execution_count="1">
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<div class="sourceCode cell-code" id="cb1"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb1-1"><a href="#cb1-1" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> cv2</span>
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<span id="cb1-2"><a href="#cb1-2" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> matplotlib.pyplot <span class="im">as</span> plt</span>
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</div>
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<div class="sourceCode cell-code" id="cb2"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb2-1"><a href="#cb2-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Overlay transparently</span></span>
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<span id="cb2-2"><a href="#cb2-2" aria-hidden="true" tabindex="-1"></a>combined <span class="op">=</span> cv2.addWeighted(original,<span class="fl">0.4</span>,overlay_resize,<span class="fl">0.1</span>,<span class="dv">0</span>)</span>
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</section>
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<h2 class="anchored" data-anchor-id="timings">Timings</h2>
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<div id="df1bb7a2" class="cell" data-execution_count="3">
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<div class="sourceCode cell-code" id="cb3"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb3-1"><a href="#cb3-1" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> sys</span>
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<span id="cb3-3"><a href="#cb3-3" aria-hidden="true" tabindex="-1"></a><span class="im">from</span> timings <span class="im">import</span> calculate_times</span>

evaluation/posts/2024_06_03/index.html

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<h2 class="anchored" data-anchor-id="timings">Timings</h2>
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<div id="f6b2e6ee" class="cell" data-execution_count="1">
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<div class="sourceCode cell-code" id="cb1"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb1-1"><a href="#cb1-1" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> sys</span>
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<span id="cb1-3"><a href="#cb1-3" aria-hidden="true" tabindex="-1"></a><span class="im">from</span> timings <span class="im">import</span> calculate_times</span>

evaluation/posts/2024_06_05/index.html

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<h3 class="anchored" data-anchor-id="comparing-best-practice-audit-results-with-monks-and-harper">Comparing best practice audit results with Monks and Harper</h3>
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<p>Compared my decisions for the best practice audit against those made in Monks and Harper.</p>
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<p>Their GitHub is <a href="https://github.com/TomMonks/des_sharing_lit_review">TomMonks/des_sharing_lit_review</a>, which provides the file <code>bp_audit.zip</code>. I used the provided code to clean this and saved it as <code>bp_audit_clean.csv</code>, which can then view here:</p>
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<div class="sourceCode cell-code" id="cb1"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb1-1"><a href="#cb1-1" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> pandas <span class="im">as</span> pd</span>
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<span id="cb1-3"><a href="#cb1-3" aria-hidden="true" tabindex="-1"></a><span class="co"># Import review results</span></span>

evaluation/reproduction_report.html

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<div class="quarto-title-meta-heading">Published</div>
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<p class="date">6th June 2024</p>
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<div class="block-title">Abstract</div>
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<p>This is a plain english summary for this reproduction report</p>
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</div>
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<p>Allen, M., Bhanji, A., Willemsen, J., Dudfield, S., Logan, S., &amp; Monks, T. <strong>A simulation modelling toolkit for organising outpatient dialysis services during the COVID-19 pandemic</strong>. <em>PLoS One</em> 15, 8 (2020). <a href="https://doi.org/10.1371%2Fjournal.pone.0237628" class="uri">https://doi.org/10.1371%2Fjournal.pone.0237628</a>.</p>
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<p>Manuscript title:</p>
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<p>Authors (with email + orcid if known):</p>
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<p>Summary of paper:</p>
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<p>Links (DOI/URL) to everything available for that article (pre-reg, article, supplementary, code):</p>
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<p>Cite the protocol used for reproduction.</p>
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<p>Scope of reproducibility report:</p>
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<ul>
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<li>The overall reproduction success of the paper can be described as the proportion of items from the scope that were determined to be reproduced (e.g.&nbsp;4 out of 5, 80%). This provides more context than just stating that a paper was or was not reproduced. When describing the reproduction success, it is important to include context on troubleshooting steps required (such as writing new code or contacting the author).</li>
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</ul>
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<p>Results:</p>
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<ul>
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<li>Reproduction success</li>
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<li>Evaluation (against sharing, badges, and reporting guidelines)</li>
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</ul>
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<p><strong>Study:</strong> Allen, M., Bhanji, A., Willemsen, J., Dudfield, S., Logan, S., &amp; Monks, T. A simulation modelling toolkit for organising outpatient dialysis services during the COVID-19 pandemic. <em>PLoS One</em> 15, 8 (2020). <a href="https://doi.org/10.1371%2Fjournal.pone.0237628" class="uri">https://doi.org/10.1371%2Fjournal.pone.0237628</a>.</p>
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<p><strong>Model:</strong> Discrete-event simulation, dialysis units during COVID-19, keeping COVID positive and negative patients seperate</p>
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<p><strong>Contributors:</strong> Amy Heather (reproduction), Tom Monks (advice).</p>
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<p><strong>Scope:</strong> Three figures</p>
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<p><strong>Reproduction success:</strong> 3 of 3 (100%)</p>
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<p><strong>Evaluation against guidelines:</strong></p>
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<table class="caption-top table">
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<colgroup>
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<col style="width: 24%">
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<col style="width: 15%">
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<col style="width: 12%">
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<col style="width: 17%">
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<col style="width: 10%">
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<col style="width: 18%">
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</colgroup>
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<thead>
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<tr class="header">
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<th>Category</th>
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<th>Total Items</th>
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<th>Fully Met</th>
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<th>Partially Met</th>
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<th>Not Met</th>
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<th>Not Applicable</th>
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</tr>
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</thead>
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<tbody>
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<tr class="odd">
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<td>Best Practice Audit</td>
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<td>11</td>
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<td>9</td>
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<td>1</td>
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<td>1</td>
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<td>-</td>
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</tr>
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<td>STARS (Essential)</td>
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<td>7</td>
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<td>5</td>
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<td>1</td>
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<td>1</td>
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<td>-</td>
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</tr>
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<td>STARS (Optional)</td>
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<td>5</td>
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<td>1</td>
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<td>-</td>
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<td>4</td>
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<td>-</td>
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</tr>
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<tr class="even">
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<td>Badges (Criteria)</td>
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<td>12</td>
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<td>9</td>
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<td>-</td>
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<td>3</td>
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<td>-</td>
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</tr>
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<td>Badges (Badges)</td>
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<td>12</td>
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<td>10</td>
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<td>-</td>
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<td>2</td>
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<td>-</td>
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</tr>
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<tr class="even">
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<td>STRESS-DES</td>
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<td>24</td>
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<td>15</td>
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<td>3</td>
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<td>4</td>
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<td>2</td>
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</tr>
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<tr class="odd">
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<td>ISPOR-SDM</td>
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<td>18</td>
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<td>14</td>
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<td>1</td>
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<td>1</td>
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<td>2</td>
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</tr>
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</tbody>
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</table>
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search.json

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"href": "evaluation/reproduction_report.html",
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"title": "Computational reproducibility report",
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"text": "Allen, M., Bhanji, A., Willemsen, J., Dudfield, S., Logan, S., & Monks, T. A simulation modelling toolkit for organising outpatient dialysis services during the COVID-19 pandemic. PLoS One 15, 8 (2020). https://doi.org/10.1371%2Fjournal.pone.0237628.\nManuscript title:\nAuthors (with email + orcid if known):\nSummary of paper:\nLinks (DOI/URL) to everything available for that article (pre-reg, article, supplementary, code):\nCite the protocol used for reproduction.\nScope of reproducibility report:\n\nThe overall reproduction success of the paper can be described as the proportion of items from the scope that were determined to be reproduced (e.g. 4 out of 5, 80%). This provides more context than just stating that a paper was or was not reproduced. When describing the reproduction success, it is important to include context on troubleshooting steps required (such as writing new code or contacting the author).\n\nResults:\n\nReproduction success\nEvaluation (against sharing, badges, and reporting guidelines)"
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"text": "Study: Allen, M., Bhanji, A., Willemsen, J., Dudfield, S., Logan, S., & Monks, T. A simulation modelling toolkit for organising outpatient dialysis services during the COVID-19 pandemic. PLoS One 15, 8 (2020). https://doi.org/10.1371%2Fjournal.pone.0237628.\nModel: Discrete-event simulation, dialysis units during COVID-19, keeping COVID positive and negative patients seperate\nContributors: Amy Heather (reproduction), Tom Monks (advice).\nScope: Three figures\nReproduction success: 3 of 3 (100%)\nEvaluation against guidelines:\n\n\n\n\n\n\n\n\n\n\n\nCategory\nTotal Items\nFully Met\nPartially Met\nNot Met\nNot Applicable\n\n\n\n\nBest Practice Audit\n11\n9\n1\n1\n-\n\n\nSTARS (Essential)\n7\n5\n1\n1\n-\n\n\nSTARS (Optional)\n5\n1\n-\n4\n-\n\n\nBadges (Criteria)\n12\n9\n-\n3\n-\n\n\nBadges (Badges)\n12\n10\n-\n2\n-\n\n\nSTRESS-DES\n24\n15\n3\n4\n2\n\n\nISPOR-SDM\n18\n14\n1\n1\n2"
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