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4 | 4 | <meta charset="utf-8"> |
5 | | -<meta name="generator" content="quarto-1.8.27"> |
| 5 | +<meta name="generator" content="quarto-1.9.27"> |
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7 | 7 | <meta name="viewport" content="width=device-width, initial-scale=1.0, user-scalable=yes"> |
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9 | | -<meta name="dcterms.date" content="2026-02-23"> |
| 9 | +<meta name="dcterms.date" content="2026-03-08"> |
10 | 10 | <meta name="keywords" content="preregistration, preregistration template, transparency, reproducibility, open-science"> |
11 | 11 |
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12 | 12 | <title>Ecological Modelling Preregistration Template</title> |
13 | 13 | <style> |
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55 | 57 | <link href="template_files/libs/quarto-html/tippy.css" rel="stylesheet"> |
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62 | 64 | </head> |
@@ -257,7 +259,7 @@ <h1 class="title">Ecological Modelling Preregistration Template</h1> |
257 | 259 | <div> |
258 | 260 | <div class="quarto-title-meta-heading">Published</div> |
259 | 261 | <div class="quarto-title-meta-contents"> |
260 | | - <p class="date">February 23, 2026</p> |
| 262 | + <p class="date">March 8, 2026</p> |
261 | 263 | </div> |
262 | 264 | </div> |
263 | 265 |
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@@ -1215,7 +1217,7 @@ <h2 data-number="4.1" class="anchored" data-anchor-id="model-calibration-and-val |
1215 | 1217 | </div> |
1216 | 1218 | <div id="callout-46" class="callout-46-contents callout-collapse collapse"> |
1217 | 1219 | <div class="callout-body-container callout-body"> |
1218 | | -<p>This section pertains to any data calibration, validation or testing schemes that will be implemented. For example, the model may be tested on data independent of those used to parameterise the model (external validation), or the model may be cross-validated on random sub-samples of the data used to parameterise the model <span class="citation" data-cites="Yates2018 Barnard2019">(<a href="#ref-Barnard2019" role="doc-biblioref">Barnard et al., 2019</a>; internal cross-validation <a href="#ref-Yates2018" role="doc-biblioref">Yates et al., 2018</a>)</span>. For some types of models, hyper-parameters are estimated from data, and may be tuned on further independent holdouts of the training data (“validation data”).</p> |
| 1220 | +<p>This section pertains to any data calibration, validation or testing schemes that will be implemented. For example, the model may be tested on data independent of those used to parameterise the model (external validation), or the model may be cross-validated on random sub-samples of the data used to parameterise the model <span class="citation" data-cites="Yates2018 Barnard2019">(internal cross-validation <a href="#ref-Yates2018" role="doc-biblioref">Yates et al., 2018</a>; <a href="#ref-Barnard2019" role="doc-biblioref">Barnard et al., 2019</a>)</span>. For some types of models, hyper-parameters are estimated from data, and may be tuned on further independent holdouts of the training data (“validation data”).</p> |
1219 | 1221 | </div> |
1220 | 1222 | </div> |
1221 | 1223 | </div> |
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