Review of the assessment framework for Atlantic Cod in NAFO 3Pn4RS : population modelling and elements relevant to a renewed precautionary approach and rebuilding plan
Bibliographic record
Abstract
Fisheries and Oceans Canada in the Quebec region undertook in 2021-2022 a review of the assessment framework for the Northwest Atlantic Fisheries Organization (NAFO) 3Pn4RS Atlantic cod (Gadus morhua) stock in the northern Gulf of St. Lawrence. A review of assessment inputs, including information on reported and non-reported fishery catches, tagging information and fishery independent monitoring results took place in the spring of 2021. The present document supports the second part of the framework review, which took place in May 2022. That meeting examined some additional assessment model inputs and modelling considerations and principally examined a proposed new model for the assessment of the 3Pn4RS cod stock. The current research document presents the details of that new model and associated model results, as well as results for alternative model formulations, some limited simulation tests and sensitivity evaluations for key model assumptions. We also present methodology for model projections and discuss key uncertainties related to projections of future stock status, particularly as they relate to longer term projections required as part of rebuilding planning. Finally, we review the information available at the time to define revised reference points for the management of the stock and to support the development of a new rebuilding plan for the stock.
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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 | 0.010 | 0.011 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".