Foraging Ecology and Population Dynamics of Collared Pikas in Southwestern Yukon
Bibliographic record
Abstract
THE FORAGING DECISIONS MADE BY HERBIVORES influ-ence population dynamics through their effects onenergy gain, energy expenditure, and ultimately, survival (McNamara and Houston, 1997). In turn, foraging by herbivores may influence the amount of vegetation available for the future. Therefore, herbivores and vegeta-tion often are coupled in a strong reciprocal relationship: the abundance of one affects the abundance of the other through time (e.g., Caughley, 1976). This interaction is particularly important for herbivores living in seasonal environments where food abundance and quality vary dramatically between growing and winter seasons. Herbivores must adapt their foraging behaviour to contend with these changes and survive until the follow-ing growing season (Owen-Smith, 2002). In addition to seasonal effects, daily foraging decisions are constrained by a number of other factors, which may be classified as
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".