Survival and Body Condition of Raccoons at the Edge of the Range
Bibliographic record
Abstract
ABSTRACT We investigated the influence of intrinsic and extrinsic variables on overwinter survival of raccoons ( Procyon lotor; n = 114) at the northern edge of their distribution. A Cox proportional hazard model identified winter severity as the variable with the greatest influence on raccoon survival (β = 1.08). Autumn body condition estimates (20.5 ± 0.46% total body fat) were relatively stable across years even though we observed large differences in autumn food indices. Variations in autumn body condition did not explain heterogeneity observed in overwinter survival nor the spring condition in which raccoons emerged. Relatively constant autumn body condition suggests reliable availability of anthropogenic food resources may negate variations observed in natural food items on which raccoons rely during hyperphagia. Conversely, spring body condition did vary among years and was highly correlated with winter severity. Accordingly, we also observed a strong inverse relationship with overwinter survival and winter severity. Our findings indicate winter climatic constraints are important factors governing the northern limit of raccoon distribution and changes in winter severity could have important implications in further range expansion of 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".