Food habits of wolverine<i>Gulo gulo</i>in montane ecosystems of British Columbia, Canada
Bibliographic record
Abstract
We examined the seasonal food habits of wolverine Gulo gulo in subboreal and interior wet-belt montane environments in British Columbia by analyzing scats collected during the course of two concurrent wolverine studies. Understanding foraging ecology for a wide-ranging carnivore such as the wolverine is important, particularly because reproduction has been demonstrated to be closely linked to food abundance. Wolverine diet was shown to vary regionally and seasonally. Regional variation was related to differences in prey availability between study areas. Moose Alces alces, caribou Rangifer tarandus, and hoary marmots Marmota caligata were abundant and common prey items within both study areas. Mountain goats Oreamnos americanus and porcupine Erithizon dorsatum were more abundant and more frequent prey items in the Columbia Mountains, while snowshoe hare Lepus americanus and beaver Castor canadensis were more abundant and more frequent prey items in the Omineca Mountains. Within the winter season, diet choices by reproductive females were different than other sex and age classes. Caribou, hoary marmots and porcupines were found in significantly higher frequencies in the diet of reproductive females. Foraging observations concurred with the findings of scat analyses. Dependence of reproductive females on a species of current conservation concern (caribou) and one which could be affected by issues related to climate change (hoary marmot) may present conservation issues for wolverines in the future.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| 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".