Groups of foraging North Atlantic right whales occur under diverse prey field conditions in the southwestern Gulf of St. Lawrence, Canada
Bibliographic record
Abstract
The southwestern Gulf of St. Lawrence (swGSL), Canada, is a foraging habitat for endangered North Atlantic right whales Eubalaena glacialis (NARWs). Late-stage copepods of the genus Calanus are NARW prey, and 3 Calanus species are present in the swGSL. We aimed to characterize spatiotemporal patterns in Calanus and environmental conditions associated with groups of foraging NARWs in 2 valleys of the swGSL, and to evaluate correlations between conditions and whale sighting rates. Over 3 years, we conducted day/night oceanographic profiling and whale surveys at 17 stations during July and August. C. finmarchicus and C. hyperboreus dominated the prey field in proportions that varied among stations, with less contribution from C. glacialis . Calanus layers typically occurred between 18 and 40 m subsurface and/or within 12 m of the seafloor. Three general vertical distributional patterns of Calanus were observed: a single subsurface layer, a single deep layer, or both subsurface and deep layers. Patterns corresponded with prey species composition and activity state (i.e. active or diapausing) within a station. Environmental conditions did not explain variation in whale sighting rates among stations. These results imply that NARWs regularly adjust their dive depth to exploit Calanus layers throughout the water column in the swGSL, except very close to the surface where prey concentrations are generally low. No single environmental context observed in our study can fully explain the diet, behavior, or distribution of NARWs in the swGSL, where multiple prey species likely increase the breadth of possible foraging conditions relative to more southerly, warmer habitats where C. finmarchicus alone dominates.
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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 | 0.001 |
| 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".