Preliminary estimates of annual capelin consumption by Atlantic cod and Greenland halibut
Bibliographic record
Abstract
In order to obtain a fishery-independent index covering a significant portion of the Gulf of St. Lawrence (GSL, NAFO Divisions 4RST) capelin (Mallotus spp.) stock area, the stomach contents of Atlantic cod (Gadus morhua) and Greenland halibut (Reinhardtius hippoglossoides) collected during the summer nGSL multispecies survey were examined. Using a bioenergetics approach, it was estimated that annual capelin consumption by the two predators continued to be higher than the commercial landings recorded for the GSL. These results support those obtained from previously published ecosystem models. All length classes combined, the percentage of capelin in the mean stomach contents of Atlantic cod shows greater interannual variation compared to the stomach contents of Greenland halibut. The use of capelin by Greenland halibut more closely reflected changes in the average number of capelin caught per tow in the nGSL multispecies surveys in years for which fish stomachs were available. However, several sources of uncertainty were raised regarding the stomach content data used and some of the assumptions in the methodology, and the need to collect samples at other times of the year was pointed out. Since capelin is one of the major forage species in the GSL, considering the population patterns of its predators and assessing their consumption of capelin would be additional aspects of interest to include in the assessment of this species.
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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 | 0.001 |
| 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 | 0.000 | 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".