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          <dc:title>&lt;p&gt;Predicted feeding time proportions from manually-validated and Supported Vector Machine (SVM) model output, compared to classification using dive shape [58]. We derived false positive and negative rates of feeding detection for dive shape relative to SVM and manually audited video data.&lt;/p&gt;</dc:title>
          <dc:creator>Jay Kirkham (24998561)</dc:creator>
          <dc:creator>Kimberley T.A. Davies (24998564)</dc:creator>
          <dc:creator>Heather J. Foley (6256202)</dc:creator>
          <dc:creator>Chris Zadra (24998567)</dc:creator>
          <dc:creator>Rhyl Frith (24998570)</dc:creator>
          <dc:creator>Paolo S. Segre (3256308)</dc:creator>
          <dc:creator>Sarah M.E. Fortune (21567673)</dc:creator>
          <dc:subject>Environmental Sciences not elsewhere classified</dc:subject>
          <dc:subject>Ecology</dc:subject>
          <dc:subject>Biological Sciences not elsewhere classified</dc:subject>
          <dc:subject>Science Policy</dc:subject>
          <dc:subject>vessel exclusion zone</dc:subject>
          <dc:subject>train classification learners</dc:subject>
          <dc:subject>support vector machine</dc:subject>
          <dc:subject>identifying ram filtration</dc:subject>
          <dc:subject>decreased swim speed</dc:subject>
          <dc:subject>validated kinematic data</dc:subject>
          <dc:subject>tag camera footage</dc:subject>
          <dc:subject>div &gt;&lt; p</dc:subject>
          <dc:subject>4 hours day</dc:subject>
          <dc:subject>informing risk policy</dc:subject>
          <dc:subject>kinematic signature</dc:subject>
          <dc:subject>underwater behaviour</dc:subject>
          <dc:subject>time within</dc:subject>
          <dc:subject>test accuracy</dc:subject>
          <dc:subject>risk areas</dc:subject>
          <dc:subject>relevant information</dc:subject>
          <dc:subject>opened mouth</dc:subject>
          <dc:subject>open wide</dc:subject>
          <dc:subject>manual validation</dc:subject>
          <dc:subject>increased drag</dc:subject>
          <dc:subject>human activities</dc:subject>
          <dc:subject>classifying behaviour</dc:subject>
          <dc:subject>camera tags</dc:subject>
          <dc:subject>body position</dc:subject>
          <dc:subject>best performing</dc:subject>
          <dc:subject>behavioural information</dc:subject>
          <dc:subject>averaging 11</dc:subject>
          <dc:subject>9 %).</dc:subject>
          <dc:subject>1 %)</dc:subject>
          <dc:description>&lt;p&gt;Predicted feeding time proportions from manually-validated and Supported Vector Machine (SVM) model output, compared to classification using dive shape [&lt;a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0352346#pone.0352346.ref058" target="_blank"&gt;58&lt;/a&gt;]. We derived false positive and negative rates of feeding detection for dive shape relative to SVM and manually audited video data.&lt;/p&gt;</dc:description>
          <dc:date>2026-09-16T17:29:39Z</dc:date>
          <dc:type>Dataset</dc:type>
          <dc:type>Dataset</dc:type>
          <dc:identifier>10.1371/journal.pone.0352346.t002</dc:identifier>
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