2-year projections offshore scallop fishery
Bibliographic record
Abstract
Georges Bank ‘a’ (GBa) and Browns Bank North (BBn) comprise the majority of catches from the Offshore Scallop fishery in the Fisheries and Oceans Canada (DFO) Maritimes Region. Both stocks are managed using total allowable catches (TACs). The annual assessments use a modified version of a state-space delay-difference population model fit to the survey estimates of fully recruited biomass, recruit biomass, and fishery catch per unit effort. In 2020, the DFO Science Offshore Scallop survey was cancelled due to challenges associated with the COVID-19 pandemic. In the absence of survey data, two-year model projections are needed to update the stock status for 2021. The scallop stocks on GBa and BBn demonstrate substantial interannual variability in their productivity. For GBa, the surplus production rate estimates ranged from 0.25 to 0.27, which is consistent with previous values. For BBn, the surplus production rate estimates ranged from 0.13 to 0.15, which is higher than previous values. If used over the long-term to provide harvest advice, relative to the use of one-year projections, use of two-year projections as the basis for management decisions over the long term would result in substantial risk of either loss in potential catch or overharvesting. Even though the usefulness of two-year projections is limited for long-term advice, they provide context for tactical decision-making in 2021 in the absence of 2020 survey data. For GBa, for the two-year projection scenarios evaluated, the probability that the 2021 fully recruited biomass would be above the upper stock reference (USR) and in the healthy zone after removing 4,000 mt (the 2021 interim TAC) is at least 0.98 and is predicted to result in an exploitation rate between 0.08 and 0.1. For BBn, for the two-year projection scenarios evaluated, removing 300 mt (the 2021 interim TAC) is predicted to result in an exploitation rate between 0.12 and 0.14 and corresponds to an expected range of biomass change between −14% and 1%.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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".