Setting biological reference points for sea scallops (<i>Placopecten magellanicus</i>) allowing for the spatial distribution of productivity and fishing effort
Bibliographic record
Abstract
Management for the major sea scallop (Placopecten magellanicus) fisheries in Canada is based on maximum sustainable yield (MSY) biomass and fishing mortality reference points applied to the whole stock, under the assumption that fishing mortality is uniformly distributed in space. However, scallop fishing vessels concentrate fishing in areas that consistently exhibit high densities resulting in a nonuniform spatial distribution of fishing effort. This study applies a spatial model for fishing effort derived from satellite vessel monitoring system data, scallop habitat suitability maps, and relative scallop density from a spatial stock assessment model to evaluate precautionary approach reference points in support of sustainable management. Target harvest rates were evaluated in terms of MSY for the higher habitat suitability areas. The results indicated that although MSY for the spatial model were similar to those when assuming a uniform distribution of effort, the biomass and catch rates over all areas were higher. The spatial model predicted that the MSY would be taken with less fishing effort, potentially lessening the benthic impacts from the scallop fishery.
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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 | 0.002 | 0.006 |
| 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".