Licking their wounds: Social response to trauma by free‐ranging bison (<i>Bison bison</i>)
Bibliographic record
Abstract
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 <3 m of each other during this time and all of the observed wound licking occurred in <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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".