Repeated call sequences and behavioural context in long-finned pilot whales off Cape Breton, Nova Scotia, Canada
Bibliographic record
Abstract
Repeated calls are part of the vocal repertoire of a diverse array of species, often presented in sequences that take time and effort on the part of the signal producer. Rhythmic repeated call sequences make up a significant portion of long-finned pilot whale (Globicephala melas) vocal production, yet the function of these sequences has not been investigated until now. In this study, we explored the relationship between behavioural context and the presence of these vocal sequences using recordings of a population of pilot whales found off Cape Breton, Nova Scotia, Canada. We used a binomial logit-link generalized linear model to look for possible predictors of the presence of repeated call sequences. They were more common in recordings of socializing whales than in those of whales in other behavioural states, and least common in resting whales. These vocal repetitions were also more common with larger group size. These results suggest that sequences function in maintaining contact and cohesion within this social species, possibly also serving in individual or group identification. The context of repeated call sequences indicate that they are not primarily mother–calf interactions, as they are heard just as commonly from groups without young. Future studies of pilot whale repeated call sequences should include individual-level behaviour and detailed acoustic calling context.
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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 | 0.001 |
| 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) | 0.002 | 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".