Variation in blubber fatty acid composition among marine mammals in the Canadian Arctic
Bibliographic record
Abstract
Abstract The composition of predator adipose stores can provide important insights into foraging patterns and the ecological relationships among species. We determined the fatty acid (FA) composition of 843 blubber samples from 80 bearded seals (Erignathus barbatus), 33 harbor seals (Phoca vitulina), 239 harp seals (Pagophilus groenlandicus), 32 hooded seals (Cystophora cristata), 281 ringed seals (Phoca hispida), 53 walruses (Odobenus rosmarus rosmarus), 105 beluga whales (Delphinapterus leucas), and 20 narwhals (Monodon monoceros) across the Canadian Arctic to examine patterns of variability among and within species. FA signatures accurately distinguished phocid seals, walruses, and whales. Belugas and narwhals had the most similar FA signatures of any two species, suggesting substantial overlap in their diets, especially in the narwhal‐wintering area off eastern Baffin Island. Among phocid seals, harp and hooded seals had the most similar FA signatures. Bearded seals were most similar to walruses, which was consistent with the benthic feeding habits of both species. Within species, geographic differences in FA signatures were found over both large (>4,000 km) and small (<100 km) spatial scales. Overall, within‐species differences were smaller than among‐species differences. In general, FA signature patterns were consistent with previous studies of the ecology and diets of arctic marine mammals.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| 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".