Contact call diversity in natural beluga entrapments in an Arctic estuary: Preliminary evidence of vocal signatures in wild belugas
Bibliographic record
Abstract
A bstract Broadband, pulsed contact calls have been described for captive and temporarily restrained belugas, but little information exists on their usage in the wild. We examined vocal production during 14 natural beluga entrapments in a shallow channel in Cunningham Inlet, as isolation events offer ideal contexts to study contact calls. Drone footage, overhead photos, and shore‐based photos confirmed the number of individuals and age composition in each entrapment. Contact calls comprised the majority (61%) of vocalizations produced by entrapped whales compared to the free‐ranging herd (10%). We divided contact calls into complex (80%), those with a stereotyped, spectrographically prominent component overlapping the pulse train that characterizes all beluga contact calls, and simple (20%), those with no overlapping component. For each entrapment, we generated a catalogue of complex contact call types, totaling 87 types. Our classification was corroborated both quantitatively and by 55 naïve human judges. Occasional instances of overlapping contact calls of the same type indicated dyadic production. The number of contact call types per entrapment was strongly related to (never exceeding) the number of individuals, excluding neonates. Although this suggests a system of vocal signatures in belugas, consistent with their fission‐fusion society and earlier findings, whether signature identity is encoded individually or shared with related animals remains unknown.
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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 | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".