Factors influencing the diving behaviour of fish-eating killer whales: sex differences and diel and interannual variation in diving rates
Bibliographic record
Abstract
Diving behaviour of air-breathing vertebrates may be influenced by a variety of factors including age, body size, and changes in prey behaviour and (or) abundance over both short and long timescales. We studied the diving behaviour of a highly sexually dimorphic odontocete cetacean, the killer whale, Orcinus orca (L., 1758), using suction-cup-attached time-depth recorders (TDRs). We tested the hypotheses that dive rates (no. of dives/h greater than or equal to specific depths) of fish-eating killer whales varied between males and females, with age, between day and night, and among pods and years. Data were used from 34 TDR deployments between 1993 and 2002 in the inshore waters of southern British Columbia, Canada, and Washington, USA. Dive rates did not change with age or differ among pods or between males and females, although analyses restricted to adults showed that adult males dove deep significantly more frequently than adult females during the day. For all whales, dive rates and swim speeds were greater during the day than at night, suggesting decreased activity levels at night. Dive rates to deeper depths during the day decreased over the study, suggesting a long-term change in prey behaviour or abundance, though uncertainty regarding the diet of this population precludes determination of the cause of such changes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".