SOCIAL ORGANIZATION AND SPACE USE OF COYOTES IN EASTERN CANADA RELATIVE TO PREY DISTRIBUTION AND ABUNDANCE
Bibliographic record
Abstract
Abstract We studied the influence of prey size and abundance on social organization and space use by eastern coyotes (Canis latrans) in 2 areas of Nova Scotia, Canada. Breeding pairs formed the nucleus of coyote social groups, and these often traveled with 1–3 other coyotes during winter. Increased use of white-tailed deer (Odocoileus virginianus) was insufficient to explain group size and cohesiveness by eastern coyotes. Winter-traveling group size was similar for family groups using deer (X̄ = 2.6) or snowshoe hares (X̄ = 2.7) as a primary prey in winter. Estimated densities of coyotes in winter was 4.3–13.9 coyotes/100 km2. Coyotes used the same general areas during winter and summer and from year to year. However, territory sizes decreased with increasing densities of deer (partial r2 = 0.21, P = 0.043) and hares (partial r2 = 0.40, P = 0.007). During winter, coyotes used areas of high deer density in proportion to their availability, but in some instances, they used areas that contained few or no deer proportionately more than expected, probably because deep snow and few trails increased vulnerability of deer in these areas. Territoriality seemed to prevent coyotes from concentrating in deer wintering areas and kept the coyote : deer ratio relatively low (<1:25).
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".