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Record W4406244071 · doi:10.1016/j.anbehav.2024.12.001

Collar? I barely know her: The utility of accelerometry in measuring personality in situ for a free-ranging wild mammal

2025· article· en· W4406244071 on OpenAlexafffund
Jonas I. Sanders, Emily K. Studd, Ben Dantzer, Andrea E. Wishart, Matt Gaidica, Kathreen E. Ruckstuhl, Stan Boutin, Jeffrey E. Lane, April Robin Martinig

Bibliographic record

VenueAnimal Behaviour · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsUniversity of British Columbia, Okanagan CampusThompson Rivers UniversityUniversity of AlbertaUniversity of SaskatchewanUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaAmerican Society of MammalogistsW. Garfield Weston FoundationUniversity of AlbertaSigma XiaNational Science Foundation
KeywordsCollarRangingMammalPersonalityIn situPsychologyEcologyBiologyGeographySocial psychologyEngineering

Abstract

fetched live from OpenAlex

The study of personality in animals requires methods for quantifying consistent among-individual differences in behaviour. Typically, standardized behavioural assays are used rather than in situ tools. We evaluated whether assays and accelerometry, a relatively novel method of quantifying animal behaviour in the field, yielded similar personality measurements in a wild population of North American red squirrels, Tamiasciurus hudsonicus , by comparing among-individual correlations of behaviours across these methods. Both methods described two behavioural axes, with assays capturing activity and exploration, and accelerometry capturing foraging and movement. We found higher trait repeatability ( R ) for traits measured with assays ( R adj : adults: 0.37–0.40; yearlings: 0.18–0.48) than for traits measured with accelerometry ( R adj : adults 0.11–0.19; yearlings: 0.07–0.11). Additionally, we found a significant positive among-individual correlation between the assay behavioural axis associated with exploration and the accelerometry behavioural axis associated with foraging. We also found that the repeatability of traits measured with accelerometry was related to the amount of behavioural data captured by this method. Given that accelerometry was able to quantify animal personality in situ for adults, accelerometer collars may present a possible alternative to assays for species in which assays are impractical. Our results also underscore the importance of considering the amount of behavioural data captured by different methods when assessing trait repeatability. As researchers strive to measure behavioural variation under natural conditions, sufficient behavioural sampling remains a priority. • We evaluated whether assays and accelerometry measure similar behavioural axes. • Assays captured behaviours associated with active and exploratory behaviour. • Accelerometry captured behaviours associated with foraging and movement. • We found a positive among-individual correlation between exploration and foraging. • Accelerometry presents a possible alternative to assays when assays are impractical.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.215
Threshold uncertainty score0.400

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.044
GPT teacher head0.267
Teacher spread0.223 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2025
Admission routes2
Has abstractyes

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