update pages

index.html

@@ -83,10 +83,10 @@
       }
 </style>
 <link href="site_libs/htmltools-fill-0.5.7/fill.css" rel="stylesheet">
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+<link href="site_libs/bslib-component-css-0.6.2/components.css" rel="stylesheet">
+<script src="site_libs/bslib-tag-require-0.6.2/tag-require.js"></script>
 
 
 <link rel="stylesheet" href="styles.css">
@@ -198,7 +198,7 @@ <h2 class="anchored" data-anchor-id="why-a-forecasting-challenge">Why a forecast
 <div class="value-box-showcase html-fill-item html-fill-container"><svg xmlns="http://www.w3.org/2000/svg" viewbox="0 0 16 16" class="bi bi-graph-up " style="height:1em;width:1em;fill:currentColor;vertical-align:-0.125em;" aria-hidden="true" role="img"><path fill-rule="evenodd" d="M0 0h1v15h15v1H0V0Zm14.817 3.113a.5.5 0 0 1 .07.704l-4.5 5.5a.5.5 0 0 1-.74.037L7.06 6.767l-3.656 5.027a.5.5 0 0 1-.808-.588l4-5.5a.5.5 0 0 1 .758-.06l2.609 2.61 4.15-5.073a.5.5 0 0 1 .704-.07Z"></path></svg></div>
 <div class="value-box-area html-fill-item html-fill-container">
 <p class="value-box-title">Total forecasts submitted to the EFI-USGS Challenge</p>
-<p class="value-box-value">128</p>
+<p class="value-box-value">131</p>
 </div>
 </div>
 </div>
@@ -215,7 +215,7 @@ <h2 class="anchored" data-anchor-id="why-a-forecasting-challenge">Why a forecast
 <path d="M9.5 8a1.5 1.5 0 1 1-3 0 1.5 1.5 0 0 1 3 0z"></path></svg></div>
 <div class="value-box-area html-fill-item html-fill-container">
 <p class="value-box-title">Most recent data for model training</p>
-<div class="value-box-value html-fill-item html-fill-container">2024-03-23</div>
+<div class="value-box-value html-fill-item html-fill-container">2024-03-24</div>
 </div>
 </div>
 </div>
@@ -272,7 +272,7 @@ <h2 class="anchored" data-anchor-id="contact">Contact</h2>
 </section>
 <section id="acknowledgements" class="level2">
 <h2 class="anchored" data-anchor-id="acknowledgements">Acknowledgements</h2>
-<p>Thomas, R. Q., Boettiger, C., Carey, C. C., Dietze, M. C., Johnson, L. R., Kenney, M. A., et al.&nbsp;(2023). The NEON Ecological Forecasting Challenge. Frontiers in Ecology and the Environment, 21(3), 112–113. <a href="https://doi.org/10.1002/fee.2616">https://doi.org/10.1002/fee.2616</a> <br> <br> We thank the EFI community for feedback on the design of the Challenge. This material is based upon work supported by the National Science Foundation under Grant DEB-1926388. <br> <br> Page last updated on 2024-03-23</p>
+<p>Thomas, R. Q., Boettiger, C., Carey, C. C., Dietze, M. C., Johnson, L. R., Kenney, M. A., et al.&nbsp;(2023). The NEON Ecological Forecasting Challenge. Frontiers in Ecology and the Environment, 21(3), 112–113. <a href="https://doi.org/10.1002/fee.2616">https://doi.org/10.1002/fee.2616</a> <br> <br> We thank the EFI community for feedback on the design of the Challenge. This material is based upon work supported by the National Science Foundation under Grant DEB-1926388. <br> <br> Page last updated on 2024-03-24</p>
 
 
 </section>

search.json

@@ -11,7 +11,7 @@
     "href": "performance.html#sec-performance",
     "title": "Forecast performance",
     "section": "Most recent forecasts",
-    "text": "Most recent forecasts\nOnly the top performing models from the last 30 days are shown.\nForecasts submitted on 2024-03-22\n\nAquatics: Chlorophyll-a\nForecast summaries are available here\n\n\n\n\n\n\n:::"
+    "text": "Most recent forecasts\nOnly the top performing models from the last 30 days are shown.\nForecasts submitted on 2024-03-23\n\nAquatics: Chlorophyll-a\nForecast summaries are available here\n\n\n\n\n\n\n:::"
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     "objectID": "performance.html#forecast-analysis",
@@ -25,7 +25,7 @@
     "href": "performance.html#aggregated-scores",
     "title": "Forecast performance",
     "section": "Aggregated scores",
-    "text": "Aggregated scores\nAverage skill scores of each model across all sites.\n\nScores are shown by reference date and forecast horizon (in days).\n\nScores are averaged across all submissions of the model with a given horizon or a given reference_datetime using submissions made since 2023-03-24.\n\nLearn about the continous ranked probablity score here\n\nAquatics: chrophyll-a"
+    "text": "Aggregated scores\nAverage skill scores of each model across all sites.\n\nScores are shown by reference date and forecast horizon (in days).\n\nScores are averaged across all submissions of the model with a given horizon or a given reference_datetime using submissions made since 2023-03-25.\n\nLearn about the continous ranked probablity score here\n\nAquatics: chrophyll-a"
   },
   {
     "objectID": "targets.html",
@@ -179,7 +179,7 @@
     "href": "index.html#why-a-forecasting-challenge",
     "title": "EFI-USGS River Chlorophyll Forecasting Challenge",
     "section": "Why a forecasting challenge?",
-    "text": "Why a forecasting challenge?\nOur vision is to use forecasts to advance theory and to support natural resource management. We can begin to realize this vision by creating and analyzing a catalog of forecasts from a range of ecological systems, spatiotemporal scales, and environmental gradients.\nOur forecasting challenge is platform for the ecological and data science communities to advance skills in forecasting ecological systems and for generating forecasts that contribute to a synthetic understanding of patterns of environmental predictability. Rewards for contributing are skill advancement, joy, and potential involved in manuscripts. We do not currently crown winner nor offer financial awards.\nThe original NEON forecasting challenge has been an excellent focal project in university courses and this EFI-USGS challenge could be used as classroom projects as well.\n \n\n\n\n\n\n\n\n\n\nTotal forecasts submitted to the EFI-USGS Challenge\n128\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nMost recent data for model training\n2024-03-23\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nNumber of years of data for model training\n15.18\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nNumber of variables being forecasted\n1"
+    "text": "Why a forecasting challenge?\nOur vision is to use forecasts to advance theory and to support natural resource management. We can begin to realize this vision by creating and analyzing a catalog of forecasts from a range of ecological systems, spatiotemporal scales, and environmental gradients.\nOur forecasting challenge is platform for the ecological and data science communities to advance skills in forecasting ecological systems and for generating forecasts that contribute to a synthetic understanding of patterns of environmental predictability. Rewards for contributing are skill advancement, joy, and potential involved in manuscripts. We do not currently crown winner nor offer financial awards.\nThe original NEON forecasting challenge has been an excellent focal project in university courses and this EFI-USGS challenge could be used as classroom projects as well.\n \n\n\n\n\n\n\n\n\n\nTotal forecasts submitted to the EFI-USGS Challenge\n131\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nMost recent data for model training\n2024-03-24\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nNumber of years of data for model training\n15.18\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nNumber of variables being forecasted\n1"
   },
   {
     "objectID": "index.html#the-challenge-is-a-platform",
@@ -200,6 +200,6 @@
     "href": "index.html#acknowledgements",
     "title": "EFI-USGS River Chlorophyll Forecasting Challenge",
     "section": "Acknowledgements",
-    "text": "Acknowledgements\nThomas, R. Q., Boettiger, C., Carey, C. C., Dietze, M. C., Johnson, L. R., Kenney, M. A., et al. (2023). The NEON Ecological Forecasting Challenge. Frontiers in Ecology and the Environment, 21(3), 112–113. https://doi.org/10.1002/fee.2616   We thank the EFI community for feedback on the design of the Challenge. This material is based upon work supported by the National Science Foundation under Grant DEB-1926388.   Page last updated on 2024-03-23"
+    "text": "Acknowledgements\nThomas, R. Q., Boettiger, C., Carey, C. C., Dietze, M. C., Johnson, L. R., Kenney, M. A., et al. (2023). The NEON Ecological Forecasting Challenge. Frontiers in Ecology and the Environment, 21(3), 112–113. https://doi.org/10.1002/fee.2616   We thank the EFI community for feedback on the design of the Challenge. This material is based upon work supported by the National Science Foundation under Grant DEB-1926388.   Page last updated on 2024-03-24"
   }
 ]