Interannual Variation in Timing of Parturition and Growth of Collared Pikas (Ochotona collaris) in the Southwest Yukon
Bibliographic record
Abstract
The length of the snow-free season has a significant influence on reproduction and growth in northern alpine environments, and these life history traits may provide sensitive indicators of the responses of organisms to climate change. We examined growth rates and timing of parturition of collared pikas (Ochotona collaris) from 1995-2002 in the Ruby Range, Yukon Territory, Canada. Growth rates were best described using a Gompertz model, in which the asymptotic mass, determined from the average male and female weights, was 157 g, the growth rate constant (K) was 0.0557, and the age at inflection (I) was 18.12 days, for a birth weight of 10 g. The maximum growth rate for North American pikas (O. collaris and O. princeps) increased with latitude, with maximum growth rates being approximately one-third greater in northern populations where the snow-free season is less than three months long. The mean parturition date varied significantly among years from 3 June to 3 July, and delayed parturition was correlated with indices of high snow accumulation and, to a lesser extent, late spring snowmelt. However, parturition date did not significantly affect the subsequent over-winter survival of juveniles in this population, suggesting that pikas are able to adjust to seasonal uncertainty associated with highly variable spring conditions.
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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 | 0.000 | 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 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".