Feeding by grey seals in the Gulf of St. Lawrence and around Newfoundland
Bibliographic record
Abstract
Diet composition of grey seals in the Gulf of St. Lawrence (Gulf) and around the coast of Newfoundland, Canada, was examined using identification of otoliths recovered from digestive tracts. Prey were recovered from 632 animals. Twenty-nine different prey taxa were identified. Grey seals sampled in the northern Gulf of St. Lawrence fed mainly on capelin, mackerel, wolffish and lumpfish during the spring, but consumed more cod, sandlance and winter flounder during late summer. Overall, the southern Gulf diet was more diverse, with sandlance, Atlantic cod, cunner, white hake and Atlantic herring dominating the diet. Capelin and winter flounder were the dominant prey in grey seals sampled from the east coast of Newfoundland, while Atlantic cod, flatfish and capelin were the most important prey from the south coast. Animals consumed prey with an average length of 20.4 cm (Range 4.2-99.2 cm). Capelin were the shortest prey (Mean = 13.9 cm, SE = 0.08, N = 1126), while wolffish were the longest with the largest fish having an estimated length of 99.2 cm (Mean = 59.4, SE = 2.8, N = 63). In the early 1990s most cod fisheries in Atlantic Canada were closed because of the collapse of the stocks. Since then they have shown limited sign of recovery. Diet samples from the west coast of Newfoundland indicate a decline in the contribution of cod to the diet from the pre-collapse to the postcollapse period, while samples from the southern Gulf indicate little change in the contribution of cod.
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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".