Ontogeny of dive performance in pup and juvenile Steller sea lions in Alaska
Bibliographic record
Abstract
Development of competent diving ability is critical to obtaining nutritional independence in marine mammals such as Steller sea lions (SSLs), Eumetopias jubatus (Schreber, 1776). We studied diving performance in pup (75) and juvenile (36) SSLs using satellite data recorders. In general, dives by SSLs were brief and shallow. Overall, 82.3% of dives were <2 min long and 86.9% of dives were <10 m deep. Long (>5 min) and deep dives (>100 m) constituted only 2.49% and 0.77%, respectively, of total dives. We used linear mixed-effects models to investigate the relationships between the response variables maximum-daily-depth, time-at-depth, mean-dive-duration, dive rate, and time-at-sea and the predictor variables age, sex, population (eastern and western Alaska populations), time-of-day, and month-of-year. All response variables except dive rate were positively related (P < 0.05) to age. Dive rate declined (P < 0.001) with age. Time-of-day, month, population, sex, and some first-order interactions were all significantly (P < 0.05) related to some measure of diving performance. With large samples we were able to identify significant relationships between the response variables and the predictor variables, even though the total amount of variation explained by the models was low, because most dives were short and shallow regardless of age, sex, population, time-of-day, or month-of-year. Depths and durations of dives by juvenile animals increased throughout the range of ages studied and were similar to or greater than those previously reported for juveniles and adult females. We expect maximum depths and durations to continue to increase with age until body mass plateaus at about 10 years of age. Therefore, we expect older animals to be more efficient foragers, as they would have greater aerobic dive limits as well as more experience locating and capturing prey.
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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 | 0.001 | 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".