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+d8a4cfff

_tex/index.tex

@@ -352,8 +352,15 @@ \subsubsection{Mechanistic models}\label{mechanistic-models}
 
 \textbf{Trait-based} (Caron et al., 2022):
 
-\textbf{Graph embedding} (Strydom et al., 2023): \emph{e.g.,} (Strydom
-et al., 2022)
+\textbf{Graph embedding} (Strydom et al., 2022, 2023): At a high level
+graph embedding focuses on capturing the structural data of a network as
+opposed to a list of pairwise (\emph{i.e.,} mechanistic) interactions.
+Here specifically the embedding is preformed on a known interaction
+network and captures information as to where species (nodes) are
+positioned in a network \emph{e.g.,} are they basal prey species or top
+predators, similar to the log ratio model. In Strydom et al. (2022) the
+products of the embedding process are fed into a transfer learning
+framework for novel prediction\ldots{}
 
 I know tables are awful but in this case they may make more sense. Also
 I don't think I'm at the point where I can say that the table is
@@ -362,11 +369,12 @@ \subsubsection{Mechanistic models}\label{mechanistic-models}
 think\ldots{}
 
 \begin{longtable}[]{@{}
-  >{\raggedright\arraybackslash}p{(\columnwidth - 8\tabcolsep) * \real{0.2593}}
-  >{\raggedright\arraybackslash}p{(\columnwidth - 8\tabcolsep) * \real{0.1975}}
-  >{\raggedright\arraybackslash}p{(\columnwidth - 8\tabcolsep) * \real{0.1605}}
-  >{\raggedright\arraybackslash}p{(\columnwidth - 8\tabcolsep) * \real{0.2222}}
-  >{\raggedright\arraybackslash}p{(\columnwidth - 8\tabcolsep) * \real{0.1605}}@{}}
+  >{\raggedright\arraybackslash}p{(\columnwidth - 10\tabcolsep) * \real{0.2386}}
+  >{\raggedright\arraybackslash}p{(\columnwidth - 10\tabcolsep) * \real{0.1818}}
+  >{\raggedright\arraybackslash}p{(\columnwidth - 10\tabcolsep) * \real{0.1477}}
+  >{\raggedright\arraybackslash}p{(\columnwidth - 10\tabcolsep) * \real{0.2045}}
+  >{\raggedright\arraybackslash}p{(\columnwidth - 10\tabcolsep) * \real{0.1591}}
+  >{\raggedright\arraybackslash}p{(\columnwidth - 10\tabcolsep) * \real{0.0682}}@{}}
 \caption{Lets make a table that gives an overview of the different
 topology generators that we will look
 at}\label{tbl-history}\tabularnewline
@@ -381,6 +389,8 @@ \subsubsection{Mechanistic models}\label{mechanistic-models}
 Specificity
 \end{minipage} & \begin{minipage}[b]{\linewidth}\raggedright
 Interaction
+\end{minipage} & \begin{minipage}[b]{\linewidth}\raggedright
+Data
 \end{minipage} \\
 \midrule\noalign{}
 \endfirsthead
@@ -395,22 +405,25 @@ \subsubsection{Mechanistic models}\label{mechanistic-models}
 Specificity
 \end{minipage} & \begin{minipage}[b]{\linewidth}\raggedright
 Interaction
+\end{minipage} & \begin{minipage}[b]{\linewidth}\raggedright
+Data
 \end{minipage} \\
 \midrule\noalign{}
 \endhead
 \bottomrule\noalign{}
 \endlastfoot
-random & structural & network & species agnostic & binary \\
-cascade & structural & network & species agnostic & binary \\
-niche & structural & network & species agnostic & binary \\
-nested hierarchical & structural & network & species agnostic &
-binary \\
-ADBM & mechanistic & & energetics & quantitative \\
-log-ratio & pondering\ldots{} & & & \\
-PFIM & mechanistic & metaweb & trait based & pondering\ldots{} \\
-graph embedding & embedding & metaweb & evolutionary & probabilistic \\
-trait model & mechanistic & metaweb & trait based & \\
-stochastic & & & & \\
+random & structural & network & species agnostic & binary & \\
+cascade & structural & network & species agnostic & binary & \\
+niche & structural & network & species agnostic & binary & \\
+nested hierarchical & structural & network & species agnostic & binary
+& \\
+ADBM & mechanistic & & energetics & quantitative & \\
+log-ratio & pondering\ldots{} & & & & \\
+PFIM & mechanistic & metaweb & trait based & pondering\ldots{} & \\
+graph embedding & embedding & metaweb & evolutionary & probabilistic
+& \\
+trait model & mechanistic & metaweb & trait based & & \\
+stochastic & & & & & \\
 \end{longtable}
 
 \begin{quote}
@@ -590,6 +603,28 @@ \subsection{Qualitative stuff}\label{qualitative-stuff}
 \href{https://BecksLab.github.io/ms_t_is_for_topology/index.qmd.html}{Article
 Notebook}}
 
+\subsection{Quantitative stuff}\label{quantitative-stuff}
+
+\begin{figure}[H]
+
+\centering{
+
+\includegraphics{index_files/figure-latex/notebooks-model_quantitative-fig-topology-output-1.png}
+
+}
+
+\caption{\label{fig-topology}Real vs observed values for network summary
+statistics}
+
+\end{figure}%
+
+\textsubscript{Source:
+\href{https://BecksLab.github.io/ms_t_is_for_topology/index.qmd.html}{Article
+Notebook}}
+
+This is actually an awful way to try and summarise the data but rolling
+with it for now\ldots{}
+
 \section{Discussion}\label{discussion}
 
 I think a big take home will (hopefully) be how different approaches do

index.html

@@ -212,11 +212,12 @@ <h2 id="toc-title">Table of contents</h2>
   <li><a href="#results" id="toc-results" class="nav-link" data-scroll-target="#results"><span class="header-section-number">3</span> Results</a>
   <ul class="collapse">
   <li><a href="#qualitative-stuff" id="toc-qualitative-stuff" class="nav-link" data-scroll-target="#qualitative-stuff"><span class="header-section-number">3.1</span> Qualitative stuff</a></li>
+  <li><a href="#quantitative-stuff" id="toc-quantitative-stuff" class="nav-link" data-scroll-target="#quantitative-stuff"><span class="header-section-number">3.2</span> Quantitative stuff</a></li>
   </ul></li>
   <li><a href="#discussion" id="toc-discussion" class="nav-link" data-scroll-target="#discussion"><span class="header-section-number">4</span> Discussion</a></li>
   <li><a href="#references" id="toc-references" class="nav-link" data-scroll-target="#references">References</a></li>
   </ul>
-<div class="quarto-alternate-notebooks"><h2>Notebooks</h2><ul><li><a href="notebooks/model_qualitative-preview.html"><i class="bi bi-journal-code"></i>Qualitative approach to topology generators</a></li></ul></div></nav>
+<div class="quarto-alternate-notebooks"><h2>Notebooks</h2><ul><li><a href="notebooks/model_qualitative-preview.html"><i class="bi bi-journal-code"></i>Qualitative approach to topology generators</a></li><li><a href="notebooks/model_quantitative-preview.html"><i class="bi bi-journal-code"></i>Quantitative approach to topology generators</a></li></ul></div></nav>
 </div>
 <div id="quarto-margin-sidebar" class="sidebar margin-sidebar zindex-bottom">
 </div>
@@ -271,7 +272,7 @@ <h4 data-number="2.1.2" class="anchored" data-anchor-id="mechanistic-models"><sp
 <p><strong>Stochastic</strong> <span class="citation" data-cites="rossbergFoodWebsExperts2006">(<a href="#ref-rossbergFoodWebsExperts2006" role="doc-biblioref">Rossberg et al. 2006</a>)</span>:</p>
 <p><strong>PFIM</strong> <span class="citation" data-cites="shawFrameworkReconstructingAncient2024">(<a href="#ref-shawFrameworkReconstructingAncient2024" role="doc-biblioref">Shaw et al. 2024</a>)</span>:</p>
 <p><strong>Trait-based</strong> <span class="citation" data-cites="caronAddressingEltonianShortfall2022">(<a href="#ref-caronAddressingEltonianShortfall2022" role="doc-biblioref">Caron et al. 2022</a>)</span>:</p>
-<p><strong>Graph embedding</strong> <span class="citation" data-cites="strydomGraphEmbeddingTransfer2023">(<a href="#ref-strydomGraphEmbeddingTransfer2023" role="doc-biblioref">Strydom et al. 2023</a>)</span>: <em>e.g.,</em> <span class="citation" data-cites="strydomFoodWebReconstruction2022">(<a href="#ref-strydomFoodWebReconstruction2022" role="doc-biblioref">Strydom et al. 2022</a>)</span></p>
+<p><strong>Graph embedding</strong> <span class="citation" data-cites="strydomFoodWebReconstruction2022 strydomGraphEmbeddingTransfer2023">(<a href="#ref-strydomFoodWebReconstruction2022" role="doc-biblioref">Strydom et al. 2022</a>, <a href="#ref-strydomGraphEmbeddingTransfer2023" role="doc-biblioref">2023</a>)</span>: At a high level graph embedding focuses on capturing the structural data of a network as opposed to a list of pairwise (<em>i.e.,</em> mechanistic) interactions. Here specifically the embedding is preformed on a known interaction network and captures information as to where species (nodes) are positioned in a network <em>e.g.,</em> are they basal prey species or top predators, similar to the log ratio model. In <span class="citation" data-cites="strydomFoodWebReconstruction2022">Strydom et al. (<a href="#ref-strydomFoodWebReconstruction2022" role="doc-biblioref">2022</a>)</span> the products of the embedding process are fed into a transfer learning framework for novel prediction…</p>
 <p>I know tables are awful but in this case they may make more sense. Also I don’t think I’m at the point where I can say that the table is complete/comprehensive but it getting there Not sure about putting in some papers that have used the model - totes happy to drop those I think…</p>
 <div id="tbl-history" class="quarto-float anchored">
 <figure class="quarto-float quarto-float-tbl figure">
@@ -281,11 +282,12 @@ <h4 data-number="2.1.2" class="anchored" data-anchor-id="mechanistic-models"><sp
 <div aria-describedby="tbl-history-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
 <table class="table">
 <colgroup>
-<col style="width: 25%">
-<col style="width: 19%">
-<col style="width: 16%">
-<col style="width: 22%">
-<col style="width: 16%">
+<col style="width: 23%">
+<col style="width: 18%">
+<col style="width: 14%">
+<col style="width: 20%">
+<col style="width: 15%">
+<col style="width: 6%">
 </colgroup>
 <thead>
 <tr class="header">
@@ -294,6 +296,7 @@ <h4 data-number="2.1.2" class="anchored" data-anchor-id="mechanistic-models"><sp
 <th>End product</th>
 <th>Specificity</th>
 <th>Interaction</th>
+<th>Data</th>
 </tr>
 </thead>
 <tbody>
@@ -303,69 +306,79 @@ <h4 data-number="2.1.2" class="anchored" data-anchor-id="mechanistic-models"><sp
 <td>network</td>
 <td>species agnostic</td>
 <td>binary</td>
+<td></td>
 </tr>
 <tr class="even">
 <td>cascade</td>
 <td>structural</td>
 <td>network</td>
 <td>species agnostic</td>
 <td>binary</td>
+<td></td>
 </tr>
 <tr class="odd">
 <td>niche</td>
 <td>structural</td>
 <td>network</td>
 <td>species agnostic</td>
 <td>binary</td>
+<td></td>
 </tr>
 <tr class="even">
 <td>nested hierarchical</td>
 <td>structural</td>
 <td>network</td>
 <td>species agnostic</td>
 <td>binary</td>
+<td></td>
 </tr>
 <tr class="odd">
 <td>ADBM</td>
 <td>mechanistic</td>
 <td></td>
 <td>energetics</td>
 <td>quantitative</td>
+<td></td>
 </tr>
 <tr class="even">
 <td>log-ratio</td>
 <td>pondering…</td>
 <td></td>
 <td></td>
 <td></td>
+<td></td>
 </tr>
 <tr class="odd">
 <td>PFIM</td>
 <td>mechanistic</td>
 <td>metaweb</td>
 <td>trait based</td>
 <td>pondering…</td>
+<td></td>
 </tr>
 <tr class="even">
 <td>graph embedding</td>
 <td>embedding</td>
 <td>metaweb</td>
 <td>evolutionary</td>
 <td>probabilistic</td>
+<td></td>
 </tr>
 <tr class="odd">
 <td>trait model</td>
 <td>mechanistic</td>
 <td>metaweb</td>
 <td>trait based</td>
 <td></td>
+<td></td>
 </tr>
 <tr class="even">
 <td>stochastic</td>
 <td></td>
 <td></td>
 <td></td>
 <td></td>
+<td></td>
 </tr>
 </tbody>
 </table>
@@ -451,6 +464,26 @@ <h3 data-number="3.1" class="anchored" data-anchor-id="qualitative-stuff"><span
 </div>
 </div>
 </section>
+<section id="quantitative-stuff" class="level3" data-number="3.2">
+<h3 data-number="3.2" class="anchored" data-anchor-id="quantitative-stuff"><span class="header-section-number">3.2</span> Quantitative stuff</h3>
+<div class="quarto-embed-nb-cell">
+<div id="cell-fig-topology" class="cell">
+<div class="cell-output cell-output-display">
+<div id="fig-topology" class="quarto-figure quarto-figure-center quarto-float anchored" alt="TODO">
+<figure class="quarto-float quarto-float-fig figure">
+<div aria-describedby="fig-topology-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
+<a href="index_files/figure-html/notebooks-model_quantitative-fig-topology-output-1.png" class="lightbox" data-gallery="quarto-lightbox-gallery-2" title="Figure&nbsp;2: Real vs observed values for network summary statistics"><img src="index_files/figure-html/notebooks-model_quantitative-fig-topology-output-1.png" class="img-fluid figure-img" alt="TODO"></a>
+</div>
+<figcaption class="quarto-float-caption-bottom quarto-float-caption quarto-float-fig" id="fig-topology-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
+Figure&nbsp;2: Real vs observed values for network summary statistics
+</figcaption>
+</figure>
+</div>
+</div>
+</div>
+</div>
+<p>This is actually an awful way to try and summarise the data but rolling with it for now…</p>
+</section>
 </section>
 <section id="discussion" class="level2" data-number="4">
 <h2 data-number="4" class="anchored" data-anchor-id="discussion"><span class="header-section-number">4</span> Discussion</h2>
@@ -963,7 +996,7 @@ <h2 class="unnumbered anchored" data-anchor-id="references">References</h2>
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