Mass change in Antarctic fur seal (<i>Arctocephalus gazella</i>) pups in relation to maternal characteristics at the Kerguèlen Islands
Bibliographic record
Abstract
Maternal allocation to growth of the pup was measured in Antarctic fur seals (Arctocephalus gazella) at the Kerguèlen Islands during the 1997 austral summer. Absolute mass gain of pups following a maternal foraging trip was independent of the sex of the pup but was positively related to foraging-trip duration and maternal length. However, daily mass gain (i.e., absolute mass gain of the pup divided by foraging-trip duration) decreased with increasing foraging-trip duration but increased with maternal length. While the pup were fasting, their daily mass loss was related to their sex and initial body mass: both heavier pups and female pups lost more mass per day than lighter pups and male pups. The mass-specific rate of mass loss was significantly higher in female than in male pups. Over the study period, the mean growth rate was zero, with no difference between female and male pups. The growth rate in mass of the pup was positively related to maternal length but not to maternal condition, and negatively related to the foraging-trip duration of the mother and the initial mass of the pup. This indicates that during the study period, heavier pups grew more slowly because of their higher rate of daily mass loss during periods of fasting. Interestingly, for a given maternal length, the mean mass of the pup during the study period was higher for male than for female pups, even though the rate of daily mass gain was the same. Such differences are likely to result from sex differences in the mass-specific rate of mass loss. As female pups lose a greater proportion of their mass per day, a zero growth rate (i.e., mass gain only compensating for mass loss) is reached at a lower mass in female pups than in male pups. Our results indicate that maternal allocation does not differ according to the sex of the pup, but suggest that the two sexes follow different growth strategies.
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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 | 0.000 |
| 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".