Gulf of St. Lawrence (4RST) Atlantic Halibut Stock Assessment in 2024
Bibliographic record
Abstract
Status The 2024 exploitable biomass is estimated at 81,392 t, and is above the proposed upper stock reference (USR) with a very high probability, placing the stock in the Healthy Zone of the Precautionary Approach. The fishing mortality rate (F) in 2024 is estimated at 0.03 and is below the maximum sustainable yield exploitation rate (Fmsy) estimated by the model with a very high probability. Trends Exploitable biomass has been increasing since the early 2000s, and is currently at its highest level since 1983. Recruitment has been stable at high levels since 2010. Fishing mortality rate (F) has been stable since 2012, at around 30% of Fmsy. Ecosystem and Climate Change Considerations The observed rise in water temperatures in the Gulf of St. Lawrence does not appear to be adversely affecting the survival and development of Atlantic halibut. Warming could continue to improve habitat conditions. Stock Advice Constant catch scenarios (2,466 to 4,932 t) indicate, with probabilities greater than 99%, that exploitable biomass will remain above the proposed USR over the two projected years (2025-26 and 2026-27). Under these catch scenarios, exploitable biomass would vary between a 4% increase and a 3% decrease over two years. The fishing mortality rates (F) corresponding to the catch scenarios evaluated all remain under Fmsy.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".