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Record W2053826398 · doi:10.1080/1357650x.2010.485202

Right paw foraging bias in wild black bear (<i>Ursus americanus kermodei</i>)

2011· article· en· W2053826398 on OpenAlexaff
T. E. Reimchen, M. A. Spoljaric

Bibliographic record

VenueLaterality Asymmetries of Body Brain and Cognition · 2011
Typearticle
Languageen
FieldNeuroscience
TopicHemispheric Asymmetry in Neuroscience
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsUrsusForagingLateralityPredationCarnivoreBiologyForelimbZoologyUrsus maritimusEcologyAnatomyDemographyPopulation

Abstract

fetched live from OpenAlex

Using field observations of ~15 wild adult black bear (Ursus americanus kermodei) foraging on a salmon stream during two autumns on the central coast of British Columbia, we tested for laterality of forelimb use during lunging and during handling of salmon. Of 288 lunging events observed overall, 53% were non biased, 26% were right-limb biased, and 21% left-limb biased (p = .53 between left and right bias). Among six bears in which we could ascertain individual identity (182 lunging events), there was heterogeneity among individuals (p <.05) of which two were significantly right biased and one significantly left biased (p<.005). Of 186 carcass-handling (pick-up) events, 68% were right-pawed (p <.005) and there was no heterogeneity among five individually identifiable bears (p = .19). There was no forelimb laterality in adjustment of the prey in the mouth or in securing the prey to the substrate. This is the first report of task-specific behavioural lateralisation of a wild carnivore and is suggestive of a right bias (left-hemisphere dominance) in object manipulation.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.102
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.059
GPT teacher head0.272
Teacher spread0.214 · 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.

Study designBench or experimental
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

Citations16
Published2011
Admission routes1
Has abstractyes

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