Variation in body mass and food intake of northern fur seals (<i>Callorhinus ursinus</i>)
Bibliographic record
Abstract
Abstract Estimates of prey and energy consumption are important for effective management and conservation of marine mammals and the ecosystems they inhabit. We used routinely collected husbandry data on body mass, food intake (kilograms), and energy intake (megajoules) from northern fur seals (Callorhinus ursinus) in zoological institutions to examine how these variables changed throughout the year, and with age, sex, and reproduction. Fur seals exhibited seasonal changes in all three variables, but the magnitude and timing of trends varied among age and sex groups. Notably, adult males exhibited rapid increases in body mass leading up to the breeding season. Fur seals were most efficient at converting energy intake to mass gain in the spring and least efficient in the fall. Intake increased into adulthood as animals grew in body mass. Sex‐specific differences in intake were detectable early in development, likely related to size dimorphism. Pregnancy was energetically inexpensive compared with lactation, with food and energy intake rapidly increasing post parturition to values that were double those during early pregnancy. This study highlights the importance of accounting for different age, sex, and life history stages when estimating prey consumption of northern fur seals.
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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".