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Incorporating sparse labels into hidden Markov models using weighted likelihoods improves accuracy and interpretability in biologging studies.

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Title: Incorporating sparse labels into hidden Markov models using weighted likelihoods improves accuracy and interpretability in biologging studies.
Authors: Sidrow, Evan1 (AUTHOR) evan.sidrow@stat.ubc.ca, Heckman, Nancy1 (AUTHOR), McRae, Tess M.2 (AUTHOR), Volpov, Beth L.2 (AUTHOR), Trites, Andrew W.2,3 (AUTHOR), Fortune, Sarah M.E.2,4 (AUTHOR), Auger-Méthé, Marie1,2 (AUTHOR)
Source: PLoS ONE. 6/18/2025, Vol. 20 Issue 6, p1-27. 27p.
Database: Academic Search Ultimate
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  Data: Incorporating sparse labels into hidden Markov models using weighted likelihoods improves accuracy and interpretability in biologging studies.
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  Data: <searchLink fieldCode="JN" term="%22PLoS+ONE%22">PLoS ONE</searchLink>. 6/18/2025, Vol. 20 Issue 6, p1-27. 27p.
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        Value: 10.1371/journal.pone.0325321
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        Text: English
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              Text: 6/18/2025
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