Quantifying allo-grooming in wild chacma baboons ( Papio ursinus ) using tri-axial acceleration data and machine learning

Charlotte Christensen; Anna M. Bracken; M. Justin O'Riain; Gaëlle Fehlmann; Mark Holton; Phillip Hopkins; Andrew J. King; Ines Fürtbauer

doi:10.1098/rsos.221103

Quantifying allo-grooming in wild chacma baboons ( Papio ursinus ) using tri-axial acceleration data and machine learning

Charlotte Christensen
, Anna M. Bracken
, M. Justin O'Riain
, Gaëlle Fehlmann
, Mark Holton
, Phillip Hopkins
, Andrew J. King
, Ines Fürtbauer

School of Biological, Earth and Environmental Sciences

Research output: Contribution to journal › Article › peer-review

Original language	Undefined/Unknown
Journal	Royal Society Open Science
DOIs	https://doi.org/10.1098/rsos.221103
Publication status	Published - Apr 2023

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10.1098/rsos.221103

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title = "Quantifying allo-grooming in wild chacma baboons ( Papio ursinus ) using tri-axial acceleration data and machine learning",

author = "Charlotte Christensen and Bracken, \{Anna M.\} and O'Riain, \{M. Justin\} and Ga{\"e}lle Fehlmann and Mark Holton and Phillip Hopkins and King, \{Andrew J.\} and Ines F{\"u}rtbauer",

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month = apr,

doi = "10.1098/rsos.221103",

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journal = "Royal Society Open Science",

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AU - Christensen, Charlotte

AU - Bracken, Anna M.

AU - O'Riain, M. Justin

AU - Fehlmann, Gaëlle

AU - Holton, Mark

AU - Hopkins, Phillip

AU - King, Andrew J.

AU - Fürtbauer, Ines

PY - 2023/4

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UR - https://doi.org/10.1098/rsos.221103

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DO - 10.1098/rsos.221103

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SN - 2054-5703

JO - Royal Society Open Science

JF - Royal Society Open Science

ER -

Quantifying allo-grooming in wild chacma baboons ( Papio ursinus ) using tri-axial acceleration data and machine learning

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