Geographic variation in simple contact calls of Canadian beluga whales <i>(Delphinapterus leucas</i>)
Bibliographic record
Abstract
Abstract Beluga whales, Delphinapterus leucas, are a highly social species with a complex and diverse vocal repertoire. Although extensively studied and classified, to date few attempts have been made to examine geographic variation in their calls. In this study, we examined geographic variation in simple contact calls (SCCs), specifically those that consist only of broadband pulsed trains, among four Canadian beluga populations from the Eastern Beaufort Sea (EBS), the Eastern High Arctic‐Baffin Bay, St. Lawrence Estuary (SLE), and the Western Hudson Bay. Five acoustic parameters were measured for each call and compared among populations using multivariate discriminant analysis. Results of our study indicate that there is a degree of variation in SCCs among these four populations, with the most geographically distant populations of the SLE and EBS displaying the greatest degrees of dissimilarity in SCC structure relative to geographically closer populations. Further, these results align with genetic variation of Canadian beluga populations previously described in the literature. This study is the first descriptive population comparison of SCCs for beluga and establishes a baseline for continued work into this developing area of research.
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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 | 0.000 |
| 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".