The effect of snow on space use of an alpine ungulate: recently fallen snow tells more than cumulative snow depth
Bibliographic record
Abstract
Snow is one of the most limiting environmental factors for large wildlife of temperate and arctic zones during winter. Snow depth may limit space use, increase energy expenditure related to movement, limit resource availability, and ultimately affect individual survival. Most of the studies on the effect of snow on animal space use have used cumulative snow depth. The amount of recently fallen snow, however, could be more relevant for wildlife, especially in alpine and northern environments, where wind shifts and hardens the snow cover constantly. From 2011 to 2013, we studied space use of mountain goats (Oreamnos americanus (Blainville, 1816)) within Jasper National Park in Alberta, Canada. During winter, daily and weekly movements decreased with the amount of recently fallen snow, but not with cumulative snow depth. These results indicate that recently fallen snow should be included in wildlife space-use studies during winter. Limited movement and range size of mountain goats also highlight the energy-saving tactic used in winter by this species.
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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".