Availability, supply, and aggregation of prey (<i>Calanus</i>spp.) in foraging areas of the North Atlantic right whale (<i>Eubalaena glacialis</i>)
Bibliographic record
Abstract
Abstract The North Atlantic right whale (NARW), Eubalaena glacialis, resides primarily on western North Atlantic continental shelves where this endangered species is susceptible to vessel strike and entanglement in fishing gear. Mitigation of these threats is dependent on the ability to predict variations in NARW occurrence. North of the Mid-Atlantic Bight, the distribution of NARWs is influenced by their prey, mainly copepods of the genus Calanus. We review factors that promote suitable foraging habitat from areas where NARWs have been observed feeding. We then synthesize our findings within a conceptual framework in which availability (i.e. shallow prey depth), supply, and aggregation of prey occur together to facilitate suitable foraging habitat. By definition, the depth of prey on the shelf is constrained to ≤200 m and other mechanisms may occur locally that further enhance prey availability. Enhanced production of prey occurs in coastal currents, which transport the copepods to NARW foraging areas. Prey concentrating mechanisms are not well-characterized. Information gaps that impede rapid and dynamic prediction of suitable foraging habitat include limited data on the spatial and temporal variation of prey and environmental conditions at local scales (i.e. 0.1–1 km), motility of prey, and diving behaviour of NARWs.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".