Assessment of Arctic Surfclam stocks in Quebec coastal waters in 2023
Bibliographic record
Abstract
Mean annual Arctic surfclam landings in Quebec totalled 683 t from 2021 to 2023, a 17% increase compared with the 2018-2020 period. The North Shore accounted for 99% of landings and the Magdalen Islands for 1%. The annual Total Allowable Catch (TAC) for the 2021 to 2023 period averaged over 80% in areas 3A and 3B. There was no fishing in areas 1A in 2022 and 2023. There was no fishing in area 1B since 2017 and areas 4C and 5A remain unexploited. The catch per unit of effort (CPUE) averages for the 2021 to 2023 period are above the time series medians (1993-2022) for areas 3A and 4A, but below the series medians for areas 1A, 2, 3B, 4B and 5B. The 2021-2023 landed surfclam size averages are above the time series medians (1993- 2022) for areas 1A, 2, 3B, 4A, 4B and 5B, but below the series medians for area 3A. The zonal exploitation rate in each area based on dredged area is below the recommended rate of 3% in all fishing areas. According to the existing decision rules, no area meets all the conditions for a quota increase, so the status quo is suggested. The fishing effort in one area should be distributed both within and among beds to limit the possibility of local overexploitation.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".