Wintering strategies by mountain goats in interior mountains
Bibliographic record
Abstract
As with many ungulates inhabiting areas with potentially deep snow, winter is an important season for mountain goats ( Oreamnos americanus (de Blainville, 1816)) and is characterized by restricted movements and high juvenile mortality. We examined winter habitat selection and wintering strategies by mountain goats in two adjacent areas of southeastern British Columbia characterized by deep, moist snow and by shallow, dry snow. Fifteen GPS collars were placed on mountain goats in each area over two winters. Winter-range size did not differ between areas and comprised, on average, 2.2%–7.4% of male home range and 8.0%–14.1% of female home range. Topographic variables dominated habitat model selection. At the broad scale, mountain goats in both areas selected winter ranges closer to escape terrain on warmer aspects that contained lesser amounts of mature dense forest. At the fine scale, mountain goats in both areas selected rugged habitat at upper mid-elevations and on warmer aspects. Alpine areas were avoided in the deep snow area and selected in the shallow snow area. No selection for mature forests was observed in either area. Mountain goats, therefore, appeared to utilize open, high-elevation habitats in shallow snow zones, but they did not seek reduced snow levels in mature forest stands in deep snow areas.
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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".