Clear diel patterns in breeding calls of harbor seals (<i>Phoca vitulina</i>) at Hornby Island, British Columbia, Canada
Bibliographic record
Abstract
During the breeding season, male harbor seals (Phoca vitulina Linnaeus, 1758) produce underwater calls for sexual advertisement. The daily and seasonal timing of these calls is influenced by female availability (i.e., tidal haul-out patterns, foraging behavior, and oestrus cycle). Therefore, temporal patterns of male calling can provide clues about patterns of female behavior. We collected underwater recordings during the 2014 breeding season at Hornby Island, British Columbia, Canada, and examined the relationships of light level, progression of breeding season, and tide relative to call presence or absence and calling rate. Calls were 15 times more likely to occur at night than during the day. Nocturnal peaks in calling rate have been observed in other harbor seal populations and have been attributed to tidal haul-out patterns and nocturnal foraging of females. In this study, tide level did not have a significant effect on calling rate, and female foraging behavior was not monitored. One acoustic observation of mammal-eating killer whale (Orcinus orca (Linnaeus, 1758)) calls was followed by 48 h of decreased calling rate. We infer that predation risk influences the temporal pattern of male calling at this location and suggest further study to support this hypothesis.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".