Review of the 2021 snow crab (Chionoecetes opilio) fishery in the southern Gulf of St. Lawrence (Areas 12, 12E, 12F and 19)
Bibliographic record
Abstract
The review of the 2021 snow crab (Chionoecetes opilio) fishery in the southern Gulf of St. Lawrence (sGSL; Areas 12, 12E, 12 F and 19) is presented. Total landings in the sGSL in 2021 were 24,479 t out of a revised quota of 24,125 t. The allowable quota in the notice to harvesters was 23,810 t. For Area 12 harvesters, landings were 20,842 t (revised quota of 20,402 t). The mean catch-per-unit-of-effort (CPUE) from logbooks increased in 2021 (57.4 kg per trap hauled (kg/th)) compared to 2020 (44.1 kg/th). In Areas 12E and 12F, landings were 296 t (revised quota of 288 t) and 1,100 t (revised quota of 1,192 t), respectively. Due to North Atlantic Right whale closures in Areas 12E and F, approximately 24.6% (73 t) and 46.2% (508 t) of the quota allocations in these Areas respectively, were fished in Area 12. In Area 12E, the mean CPUE increased in 2021 (55.7 kg/th) compared to 2020 (45.9 kg/th). In Area 12F, the mean CPUE remained high in 2021 at 59.1 kg/th, an increase compared to 2020 (45.2 kg/th). In Area 19, landings reached 2,241 t (revised quota of 2,244 t). The mean CPUE remained high in 2021 at 121.0 kg/th, an increase from 2020 (101.7 kg/th).
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".