Gender- and age-class-specific reactions to human disturbance in a sexually dimorphic ungulate
Bibliographic record
Abstract
According to optimality theory, an individual's characteristics should play a major part in determining antipredator strategies. We studied behavioural reactions to human presence of gender and age classes of 35 thinhorn sheep (Ovis dalli Nelson, 1884) in late winter 2001 in Faro, Yukon Territory, Canada. The behaviour of undisturbed sheep was observed from distances of 400–1200 m and compared with the behaviour recorded when one or two people were in close proximity to the sheep. Ewes decreased bedding and increased foraging when humans were present, but there were no changes in these behaviours in rams. Disturbance caused an increase in vigilance and a trend was found for adults to react more strongly to disturbance than juveniles. We demonstrate the importance for disturbance research of gaining detailed information about all different kinds of population members and using applicable statistical tests in the data analyses.
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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 | 0.000 | 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".