Effects of Age and Body Mass on Development of Diving Capabilities of Gray Seal Pups: Costs and Benefits of the Postweaning Fast
Bibliographic record
Abstract
Development of adequate diving capabilities is crucial for survival of seal pups and may depend on age and body size. We tracked the diving behavior of 20 gray seal pups during their first 3 mo at sea using satellite relay data loggers. We employed quantile analysis to track upper limits of dive duration and percentage time spent diving, and lower limits of surface intervals. When pups first left the breeding colony, extreme (ninety-fifth percentile) dive duration and percentage time spent diving were positively correlated with age, but not mass, at departure. Extreme dive durations and percentage time spent diving peaked at [Formula: see text] d of age at values comparable with those of adults, but were not sustained. Greater peaks in extreme percentage time spent diving occurred in pups that had higher initial values, were older at their peak, and were heavier at departure. Pups that were smaller and less capable divers when they left the colony improved extreme dive durations and percentage time spent diving more rapidly, once they were at sea. Minimum survival time correlated positively with departure mass. Pups that were heavier at weaning thus benefitted from being both larger and older at departure, but smaller pups faced a trade-off. While age at departure had a positive effect on early dive performance, departure mass impacted on peak percentage time spent diving and longer-term survival. We speculate that once small pups have attained a minimum degree of physiological development to support diving, they would benefit by leaving the colony when younger but larger to maximize limited fuel reserves, rather than undergoing further maturation on land away from potential food resources, because poor divers may be able to "catch up" once at sea.
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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".