Summer distribution and habitat preference of beluga whale social groups in the Eastern Beaufort Sea
Bibliographic record
Abstract
In social animals, group composition can cause variations in individual needs that can influence responses to habitat trade-offs, such as predator exposure or foraging opportunities. The Eastern Beaufort Sea beluga whales ( Delphinapterus leucas (Pallas, 1776)) form different group types and cover multiple habitat types in summer. This study compares the habitat preference of three beluga social group types: (1) individual belugas, (2) groups of adults, and (3) groups with at least one calf. Observations were collected during aerial surveys in July and August 2019. For each month, beluga distribution was analyzed with hierarchical generalized additive models, as a function of group type and four covariates: sea surface temperature, bathymetry, slope, and distance to the coastline. Group type, water temperature, and bathymetric features best explained beluga distribution. In July, groups of adults preferred the continental shelf, whereas individual belugas and groups with calves preferred the continental slope. In August, groups of adults and groups with calves were found in Amundsen Gulf at similar depths. For both months, individual belugas associated more with deeper and colder areas. The preferences often corresponded to previously published distributions of the beluga's main prey species, suggesting that foraging opportunities and size-related energy requirements strongly influence habitat use.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".