Spatial distribution of narwhal (<i>Monodon monoceros</i>) diving for Canadian populations helps identify important seasonal foraging areas
Bibliographic record
Abstract
In Canada, narwhals (Monodon monoceros L., 1758) are divided into the Baffin Bay (BB) and northern Hudson Bay (NHB) populations. Satellite tracking of 21 narwhals from BB and NHB provided information on their diving behaviour and was used to identify foraging regions. Previous research from hunted narwhals indicated that narwhals in both populations depend on benthic prey to meet their dietary needs. To evaluate home ranges and define areas important for benthic foraging, we conducted kernel density analysis on narwhal locations and focused on areas where deep diving occurs, as a proxy for foraging, in the winter, spring, and migratory periods. These analyses revealed important areas for foraging for BB narwhals on the summer grounds in Eclipse Sound, and the winter grounds in Davis Strait, as well as on the migratory pathway between regions. Similarly, important areas were identified for the NHB narwhal population in northwestern Hudson Bay in summer, in NHB and Hudson Strait on the migration, and to the east of the entrance to Hudson Strait in the winter. This, along with an analysis of the absolute dive depths, provides information on seasons and regions important for foraging, which is particularly relevant with increasing industrial activities in the Arctic.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 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".