Variation in survival rates for the alpine marmot (<i>Marmota marmota</i>): effects of sex, age, year, and climatic factors
Bibliographic record
Abstract
We examined variation in annual survival rates in a population of alpine marmots (Marmota marmota) according to intrinsic (sex and age) and extrinsic (year and climate) factors. We tested predictions concerning (i) a sex effect in a monogamous non-dimorphic species, (ii) age structure of survival rates in a mesomammal, and (iii) the annual variability effect and the contribution of stochastic climatic factors, especially snow cover, frost, and rainfall. We used a 8-year dataset of 367 marmots that were livetrapped and marked in La Sassière Nature Reserve in the French Alps between 1990 and 1997. Survival and recapture rates were modelled using recent developments in capturerecapture models. Sex had no effect on survival rates, which agrees with the predictions of sexual selection. Survival rates for young of the year (YOY, from weaning to first birthday) were, on average, lower than in the older age class. In the older age class, annual variation occurred that was strongly related to the intensity of autumn frost. By determining the soil temperature at the beginning of hibernation, this factor, though short-lived, could have determined the energetic cost of hibernation. Neither annual variation nor an environmental effect was detected in YOY despite a large sample size. Social thermoregulation could contribute to the stability of YOY survival rates. As infanticide was common after the immigration of a new dominant male, survival of YOY seemed to depend more on social events than on stochastic climatic ones.
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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 | 0.001 | 0.002 |
| 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) | 0.001 | 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".