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Record W4360946610 · doi:10.1111/eth.13369

Licking their wounds: Social response to trauma by free‐ranging bison (<i>Bison bison</i>)

2023· article· en· W4360946610 on OpenAlexafffund
Thomas S. Jung, Caeley Thacker, Christopher J. Lewis

Bibliographic record

VenueEthology · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsGovernment of British ColumbiaYukon Department of EnvironmentUniversity of Alberta
FundersUniversity of AlbertaGovernment of Canada
KeywordsLickingBison bisonUngulateBiologyZoologyEcology

Abstract

fetched live from OpenAlex

Abstract The epidermis of wild mammals is occasionally lacerated or punctured and wound care behaviours evolved to keep animals healthy in nature. Communal wound licking may promote healing of affected sites, relieve stress after a traumatic experience, and reinforce social bonds among individuals. Yet, there are few reported cases of communal wound licking in free‐ranging mammals. We report observations of communal wound licking in a social ungulate—free‐ranging bison ( Bison bison ). Two adult female bison presented with minor open puncture wounds after we chemically immobilized each of them with a dart fired from a rifle. The day after being darted, we observed three different adult bison lick the wounds of the two wounded bison. Both bison were &lt;3 m of each other during this time and all of the observed wound licking occurred in &lt;10 min. Our observation provides an additional example of communal wound licking in free‐ranging mammals and extends it to a social ungulate. Benefits to bison of communal wound licking are perhaps largely social. However, targeted research is needed to better understand both the frequency and cost and benefits of communal wound licking.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.527
Threshold uncertainty score0.999

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)0.0010.002

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 head0.019
GPT teacher head0.265
Teacher spread0.246 · 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 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
Published2023
Admission routes2
Has abstractyes

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