Offspring size at weaning affects survival to recruitment and reproductive performance of primiparous gray seals
Bibliographic record
Abstract
Offspring size affects survival and subsequent reproduction in many organisms. However, studies of offspring size in large mammals are often limited to effects on juveniles because of the difficulty of following individuals to maturity. We used data from a long-term study of individually marked gray seals (Halichoerus grypus; Fabricius, 1791) to test the hypothesis that larger offspring have higher survival to recruitment and are larger and more successful primiparous mothers than smaller offspring. Between 1998 and 2002, 1182 newly weaned female pups were branded with unique permanent marks on Sable Island, Canada. Each year through 2012, all branded females returning to the breeding colony were identified in weekly censuses and a subset were captured and measured. Females that survived were significantly longer offspring than those not sighted, indicating size-selective mortality between weaning and recruitment. The probability of female survival to recruitment varied among cohorts and increased nonlinearly with body mass at weaning. Beyond 51.5 kg (mean population weaning mass) weaning mass did not influence the probability of survival. The probability of female survival to recruitment increased monotonically with body length at weaning. Body length at primiparity was positively related to her body length and mass at weaning. Three-day postpartum mass (proxy for birth mass) of firstborn pups was also positively related to body length of females when they were weaned. However, females that were longer or heavier when they were weaned did not wean heavier firstborn offspring.
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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".