Assessment of the Gulf of St. Lawrence (4RST) Greenland Halibut Stock in 2024
Bibliographic record
Abstract
During the 2022-23 fishing season, preliminary landings in the Gulf of St. Lawrence totalled 930 t, representing 46% of the fixed gear allocation and the lowest value observed since 1970. Fishing effort shows a downward trend across the Gulf since 2013 and has reached the lowest level observed of the 1999-2022 period. More than 80% of estimated fishing effort was located in the western Gulf in 2022. The fishery performance index in the western Gulf has been increasing since 2018 and was around the series average in 2022. The index for the North Anticosti sector appears to be stable since 2020 and was slightly below average in 2022, while for the Esquiman sector, the index has been well below average since 2014. The length composition of landings was stable from 2019 to 2022, with the mean below the long-term average and the proportion of fish below the minimum legal size above average at about 30%. According to the three scientific surveys, the abundance and biomass indices have been on a downward trajectory since the mid-2000s. Cohorts expected to contribute to the fishery in 2023 and 2024 range from low (2016) to high (2017-2018) abundance. These cohorts have displayed a normal growth rate but their low condition in 2022 could negatively affect their growth. According to scientific surveys, the low abundance of 1-year-old individuals observed from 2020 to 2022 would have a negative impact on the biomass available for fishing in the medium term. At the Gulf scale, the exploitation rate indicator was at the lowest levels observed in 2021 and 2022. Under the precautionary approach, the stock status indicator, estimated at 33,366 t, placed the stock at the top of the cautious zone in 2022. Under the harvest control rule, all sources of removals should not exceed 2,002 t in 2023-24 and 2024-25. The Gulf of St. Lawrence is undergoing major changes: the deep waters are warming and become depleted of oxygen. In addition, changes in the structure of the community (high abundance of redfish and low abundance of prey) are observed. These changes could negatively affect the productivity of Greenland halibut. Current environmental conditions and climate projections suggest that the situation is likely to remain unfavourable.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".