Group Choice by Subadult Bighorn Rams: Trade‐offs between Foraging Efficiency and Predator Avoidance
Bibliographic record
Abstract
In addition to sexual segregation, many social ungulates show varying degrees of age segregation, especially among males. We investigated factors affecting group choice by subadult male bighorn sheep, using census data collected between 1982 and 1998 in a marked population. We examined whether group composition varied with population size and structure. Changes in total population size were correlated with the number of yearling males and yearling females, but not with the size of other sex‐age classes. In years of high population size, female groups were larger than in years of low population size, while mixed sex‐age and subadult groups showed a nonsignificant trend in the same direction. Typical group sizes of bachelor groups and the occurrence of mixed or bachelor groups were not affected by population size. When there were few subadult males in the population, groups of subadult males were less frequent than in years with many subadult males in the population, but the typical group size did not change. Subadult males were rarely seen in peer groups, and switched from female groups in spring to bachelor groups in autumn. An individual’s choice of group type is affected by its body mass, but also by the availability of enough potential group mates to provide sufficient predator‐detection efficiency.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".