Test font change

docs/404.html

@@ -6,7 +6,7 @@
   <meta http-equiv="X-UA-Compatible" content="IE=edge" />
   <title>Page not found | Modelling scenarios for nutrient-sensitive fisheries management</title>
   <meta name="description" content="Page not found | Modelling scenarios for nutrient-sensitive fisheries management" />
-  <meta name="generator" content="bookdown 0.33 and GitBook 2.6.7" />
+  <meta name="generator" content="bookdown 0.36 and GitBook 2.6.7" />
 
   <meta property="og:title" content="Page not found | Modelling scenarios for nutrient-sensitive fisheries management" />
   <meta property="og:type" content="book" />
@@ -62,6 +62,10 @@
 
 
 
+<style type="text/css">
+
+  div.hanging-indent{margin-left: 1.5em; text-indent: -1.5em;}
+</style>
 
 <link rel="stylesheet" href="style.css" type="text/css" />
 </head>

docs/data.html

@@ -6,7 +6,7 @@
   <meta http-equiv="X-UA-Compatible" content="IE=edge" />
   <title>2 Data | Modelling scenarios for nutrient-sensitive fisheries management</title>
   <meta name="description" content="2 Data | Modelling scenarios for nutrient-sensitive fisheries management" />
-  <meta name="generator" content="bookdown 0.33 and GitBook 2.6.7" />
+  <meta name="generator" content="bookdown 0.36 and GitBook 2.6.7" />
 
   <meta property="og:title" content="2 Data | Modelling scenarios for nutrient-sensitive fisheries management" />
   <meta property="og:type" content="book" />
@@ -62,6 +62,10 @@
 
 
 
+<style type="text/css">
+
+  div.hanging-indent{margin-left: 1.5em; text-indent: -1.5em;}
+</style>
 
 <link rel="stylesheet" href="style.css" type="text/css" />
 </head>

docs/distribution.html

@@ -6,7 +6,7 @@
   <meta http-equiv="X-UA-Compatible" content="IE=edge" />
   <title>4 Nutrients distribution | Modelling scenarios for nutrient-sensitive fisheries management</title>
   <meta name="description" content="4 Nutrients distribution | Modelling scenarios for nutrient-sensitive fisheries management" />
-  <meta name="generator" content="bookdown 0.33 and GitBook 2.6.7" />
+  <meta name="generator" content="bookdown 0.36 and GitBook 2.6.7" />
 
   <meta property="og:title" content="4 Nutrients distribution | Modelling scenarios for nutrient-sensitive fisheries management" />
   <meta property="og:type" content="book" />
@@ -62,6 +62,10 @@
 
 
 
+<style type="text/css">
+
+  div.hanging-indent{margin-left: 1.5em; text-indent: -1.5em;}
+</style>
 
 <link rel="stylesheet" href="style.css" type="text/css" />
 </head>

docs/index.html

@@ -6,7 +6,7 @@
   <meta http-equiv="X-UA-Compatible" content="IE=edge" />
   <title>Modelling scenarios for nutrient-sensitive fisheries management</title>
   <meta name="description" content="Modelling scenarios for nutrient-sensitive fisheries management" />
-  <meta name="generator" content="bookdown 0.33 and GitBook 2.6.7" />
+  <meta name="generator" content="bookdown 0.36 and GitBook 2.6.7" />
 
   <meta property="og:title" content="Modelling scenarios for nutrient-sensitive fisheries management" />
   <meta property="og:type" content="book" />
@@ -62,6 +62,10 @@
 
 
 
+<style type="text/css">
+
+  div.hanging-indent{margin-left: 1.5em; text-indent: -1.5em;}
+</style>
 
 <link rel="stylesheet" href="style.css" type="text/css" />
 </head>

docs/profiles.html

@@ -6,7 +6,7 @@
   <meta http-equiv="X-UA-Compatible" content="IE=edge" />
   <title>5 Timor SSF nutrient profiles | Modelling scenarios for nutrient-sensitive fisheries management</title>
   <meta name="description" content="5 Timor SSF nutrient profiles | Modelling scenarios for nutrient-sensitive fisheries management" />
-  <meta name="generator" content="bookdown 0.33 and GitBook 2.6.7" />
+  <meta name="generator" content="bookdown 0.36 and GitBook 2.6.7" />
 
   <meta property="og:title" content="5 Timor SSF nutrient profiles | Modelling scenarios for nutrient-sensitive fisheries management" />
   <meta property="og:type" content="book" />
@@ -62,6 +62,10 @@
 
 
 
+<style type="text/css">
+
+  div.hanging-indent{margin-left: 1.5em; text-indent: -1.5em;}
+</style>
 
 <link rel="stylesheet" href="style.css" type="text/css" />
 </head>
@@ -177,8 +181,8 @@ <h3><span class="header-section-number">5.2.1</span> Clusters<a href="profiles.h
 </div>
 <p>The PERMANOVA analyses (see table below) revealed statistically significant differences between clusters, suggesting robust groupings based on the nutrient profiles. The pseudo-F statistics were remarkably high in all cases, indicating strong differentiation between clusters. Specifically, the R² values were 0.86, 0.82, 0.85, and 0.92 for Atauro AG, Atauro GN, Timor AG, and Timor GN respectively, indicating that between 82% to 92% of the variance in nutrient concentrations was explained by the clusters. The high R² values underscore the distinctness of the clusters, reinforcing the validity of the K-means clustering.</p>
 <p>These findings were consistent across the datasets, with p-values below 0.001, providing clear evidence to reject the null hypothesis of no difference between clusters. Hence, the PERMANOVA results robustly support the effectiveness of the K-means algorithm in capturing meaningful patterns in nutrient profiles.</p>
-<div class="reactable html-widget html-fill-item-overflow-hidden html-fill-item" id="htmlwidget-b26055c579fa9f5c1193" style="width:auto;height:auto;"></div>
-<script type="application/json" data-for="htmlwidget-b26055c579fa9f5c1193">{"x":{"tag":{"name":"Reactable","attribs":{"data":{"subset":["atauro_AG_","atauro_AG_","atauro_AG_","atauro_GN_","atauro_GN_","atauro_GN_","timor_AG_","timor_AG_","timor_AG_","timor_GN_","timor_GN_","timor_GN_"],"term":["clusters","Residual","Total","clusters","Residual","Total","clusters","Residual","Total","clusters","Residual","Total"],"df":[4,4263,4267,4,7839,7843,4,3793,3797,4,6118,6122],"SumOfSqs":[10282.81,1696.62,11979.43,15595.87,3431.6,19027.47,24165.4,4244.24,28409.64,52086.36,4617.77,56704.14],"R2":[0.86,0.14,1,0.82,0.18,1,0.85,0.15,1,0.92,0.08,1],"statistic":[6459.27,"NA","NA",8906.63,"NA","NA",5399.05,"NA","NA",17252.06,"NA","NA"],"p.value":["< 0.001",null,null,"< 0.001",null,null,"< 0.001",null,null,"< 0.001",null,null]},"columns":[{"id":"subset","name":"subset","type":"character","align":"center","minWidth":120},{"id":"term","name":"term","type":"character","align":"center"},{"id":"df","name":"df","type":"numeric","align":"center"},{"id":"SumOfSqs","name":"SumOfSqs","type":"numeric","align":"center"},{"id":"R2","name":"R2","type":"numeric","align":"center"},{"id":"statistic","name":"statistic","type":"numeric","align":"center"},{"id":"p.value","name":"p.value","type":"character","align":"center"}],"groupBy":["subset"],"pagination":false,"defaultExpanded":true,"theme":{"color":"#222222","backgroundColor":"#ffffff","borderColor":"#dddddd","borderWidth":"1px","stripedColor":"#dddddd","highlightColor":"#f0f0f0","cellPadding":5,"tableStyle":{"fontSize":14,"borderBottom":"3px solid #222222"},"headerStyle":{"borderWidth":"3px","paddingTop":"12px","verticalAlign":"bottom","textAlign":"bottom","background":"#ffffff","textTransform":"uppercase","borderColor":"#222222","color":"#000000","&:hover":{"background":"#dddddd"},"&[aria-sort='ascending'], &[aria-sort='descending']":{"background":"#5b5e5f","color":"#ffffff"},"borderColor.1":"#333","fontSize":12},"groupHeaderStyle":{"&:not(:empty)":{"paddingBottom":"3px","verticalAlign":"bottom","textAlign":"bottom","backgroundColor":"#ffffff","textTransform":"uppercase","fontSize":12,"color":"#222222"}},"rowSelectedStyle":{"backgroundColor":"#dddddd"},"cellStyle":{"display":"flex","flexDirection":"column","justifyContent":"center"},"inputStyle":{"backgroundColor":"#ffffff","color":"#222222"},"searchInputStyle":{"textTransform":"uppercase","color":"#222222","fontSize":"14px"},"paginationStyle":{"textTransform":"uppercase","fontSize":"14px"},"pageButtonStyle":{"textTransform":"uppercase","fontSize":"14px"}},"dataKey":"2ca8f6f8fef02dca8680252b21b05b65"},"children":[]},"class":"reactR_markup"},"evals":[],"jsHooks":[]}</script>
+<div class="reactable html-widget html-fill-item-overflow-hidden html-fill-item" id="htmlwidget-515ef7e8db80151fab4d" style="width:auto;height:auto;"></div>
+<script type="application/json" data-for="htmlwidget-515ef7e8db80151fab4d">{"x":{"tag":{"name":"Reactable","attribs":{"data":{"subset":["atauro_AG_","atauro_AG_","atauro_AG_","atauro_GN_","atauro_GN_","atauro_GN_","timor_AG_","timor_AG_","timor_AG_","timor_GN_","timor_GN_","timor_GN_"],"term":["clusters","Residual","Total","clusters","Residual","Total","clusters","Residual","Total","clusters","Residual","Total"],"df":[4,4263,4267,4,7839,7843,4,3793,3797,4,6118,6122],"SumOfSqs":[10282.81,1696.62,11979.43,15595.87,3431.6,19027.47,24165.4,4244.24,28409.64,52086.36,4617.77,56704.14],"R2":[0.86,0.14,1,0.82,0.18,1,0.85,0.15,1,0.92,0.08,1],"statistic":[6459.27,"NA","NA",8906.63,"NA","NA",5399.05,"NA","NA",17252.06,"NA","NA"],"p.value":["< 0.001",null,null,"< 0.001",null,null,"< 0.001",null,null,"< 0.001",null,null]},"columns":[{"id":"subset","name":"subset","type":"character","align":"center","minWidth":120},{"id":"term","name":"term","type":"character","align":"center"},{"id":"df","name":"df","type":"numeric","align":"center"},{"id":"SumOfSqs","name":"SumOfSqs","type":"numeric","align":"center"},{"id":"R2","name":"R2","type":"numeric","align":"center"},{"id":"statistic","name":"statistic","type":"numeric","align":"center"},{"id":"p.value","name":"p.value","type":"character","align":"center"}],"groupBy":["subset"],"pagination":false,"defaultExpanded":true,"theme":{"color":"#222222","backgroundColor":"#ffffff","borderColor":"#dddddd","borderWidth":"1px","stripedColor":"#dddddd","highlightColor":"#f0f0f0","cellPadding":5,"tableStyle":{"fontSize":14,"borderBottom":"3px solid #222222"},"headerStyle":{"borderWidth":"3px","paddingTop":"12px","verticalAlign":"bottom","textAlign":"bottom","background":"#ffffff","textTransform":"uppercase","borderColor":"#222222","color":"#000000","&:hover":{"background":"#dddddd"},"&[aria-sort='ascending'], &[aria-sort='descending']":{"background":"#5b5e5f","color":"#ffffff"},"borderColor.1":"#333","fontSize":12},"groupHeaderStyle":{"&:not(:empty)":{"paddingBottom":"3px","verticalAlign":"bottom","textAlign":"bottom","backgroundColor":"#ffffff","textTransform":"uppercase","fontSize":12,"color":"#222222"}},"rowSelectedStyle":{"backgroundColor":"#dddddd"},"cellStyle":{"display":"flex","flexDirection":"column","justifyContent":"center"},"inputStyle":{"backgroundColor":"#ffffff","color":"#222222"},"searchInputStyle":{"textTransform":"uppercase","color":"#222222","fontSize":"14px"},"paginationStyle":{"textTransform":"uppercase","fontSize":"14px"},"pageButtonStyle":{"textTransform":"uppercase","fontSize":"14px"}},"dataKey":"2ca8f6f8fef02dca8680252b21b05b65"},"children":[]},"class":"reactR_markup"},"evals":[],"jsHooks":[]}</script>
 </div>
 <div id="xgboost-model-not-updated" class="section level3 hasAnchor" number="5.2.2">
 <h3><span class="header-section-number">5.2.2</span> XGBoost model (not updated)<a href="profiles.html#xgboost-model-not-updated" class="anchor-section" aria-label="Anchor link to header"></a></h3>

docs/references.html

@@ -6,7 +6,7 @@
   <meta http-equiv="X-UA-Compatible" content="IE=edge" />
   <title>References | Modelling scenarios for nutrient-sensitive fisheries management</title>
   <meta name="description" content="References | Modelling scenarios for nutrient-sensitive fisheries management" />
-  <meta name="generator" content="bookdown 0.33 and GitBook 2.6.7" />
+  <meta name="generator" content="bookdown 0.36 and GitBook 2.6.7" />
 
   <meta property="og:title" content="References | Modelling scenarios for nutrient-sensitive fisheries management" />
   <meta property="og:type" content="book" />
@@ -62,6 +62,10 @@
 
 
 
+<style type="text/css">
+
+  div.hanging-indent{margin-left: 1.5em; text-indent: -1.5em;}
+</style>
 
 <link rel="stylesheet" href="style.css" type="text/css" />
 </head>

docs/simple.html

@@ -6,7 +6,7 @@
   <meta http-equiv="X-UA-Compatible" content="IE=edge" />
   <title>6 In simple terms | Modelling scenarios for nutrient-sensitive fisheries management</title>
   <meta name="description" content="6 In simple terms | Modelling scenarios for nutrient-sensitive fisheries management" />
-  <meta name="generator" content="bookdown 0.33 and GitBook 2.6.7" />
+  <meta name="generator" content="bookdown 0.36 and GitBook 2.6.7" />
 
   <meta property="og:title" content="6 In simple terms | Modelling scenarios for nutrient-sensitive fisheries management" />
   <meta property="og:type" content="book" />
@@ -62,6 +62,10 @@
 
 
 
+<style type="text/css">
+
+  div.hanging-indent{margin-left: 1.5em; text-indent: -1.5em;}
+</style>
 
 <link rel="stylesheet" href="style.css" type="text/css" />
 </head>

docs_book/04-profiles.Rmd

@@ -176,7 +176,7 @@ timor.nutrients::perm_results %>%
 
 The model's predictive capacity was quantitatively assessed via receiver operating characteristic (ROC) analysis across five distinct clusters. The ROC curves (see [ML model interpretation][In simple terms]) illustrate a differential capacity of the model to classify each cluster based on the nutritional profiles derived from various fishing strategies. Cluster 2 and 5 demonstrated superior model performance, indicated by a curve proximate to the top-left, suggesting high sensitivity and specificity. Clusters 1 and 4 showed marginally lower but comparable discrimination ability. Cluster 3 indicated a slight decrease in sensitivity and exhibited the model's lowest performance, with a curve markedly farther from the ideal top-left position. Collectively, an aggregate AUC of 0.87 signifies a strong overall ability of the model to differentiate between the clusters, albeit with varying degrees of precision. These findings underscore the model's effectiveness in predicting nutritional outcomes based on fishing strategies, with implications for tailoring nutrient-sensitive fisheries management interventions.
 
-```{r model-settings, echo=FALSE, fig.cap="Receiver Operating Characteristic (ROC) Curves with Data Points for Cluster-Based Classification. The curves delineate the sensitivity versus 1-specificity for the five clusters derived from the XGBoost classification model. Each cluster is represented by a distinct color with data points marked, which illustrates the true positive rate against the false positive rate for each respective cluster. The closeness of each curve to the top-left corner indicates the model’s classification efficacy per cluster, with Cluster 1 and 2 showing the highest performance. The overall model demonstrates substantial predictive accuracy with a composite AUC value of 0.86.", fig.height=6, fig.width=8, message=FALSE, warning=FALSE}
+```{r model-settings, echo=FALSE, fig.cap="Receiver Operating Characteristic (ROC) Curves with Data Points for Cluster-Based Classification. The curves delineate the sensitivity versus 1-specificity for the five clusters derived from the XGBoost classification model. Each cluster is represented by a distinct color with data points marked, which illustrates the true positive rate against the false positive rate for each respective cluster. The closeness of each curve to the top-left corner indicates the model’s classification efficacy per cluster, with Cluster 1 and 2 showing the highest performance. The overall model demonstrates substantial predictive accuracy with a composite AUC value of 0.86.", fig.height=6.5, fig.width=8, message=FALSE, warning=FALSE}
 plots <-
   list(
     timor.nutrients::model_outputs$model_atauro_AG$roc_curves + ggplot2::labs(subtitle = "Atauro - All gears"),