Smaller bar spacings in a Nordmøre grid reduces the bycatch of redfish (Sebastes spp.) in the offshore Northern shrimp (Pandalus borealis) fishery of eastern Canada
Bibliographic record
Abstract
The offshore Northern shrimp (Pandalus borealis) bottom trawl fishery in eastern Canada currently uses 22 and 28 mm bar spacing Nordmøre grids to limit bycatch from using small mesh codends. However, a recent rebound of juvenile redfish (Sebastes spp.), that can pass through the grids, has greatly increased bycatch. To address this concern, this study investigated the effectiveness of 17 and 15 mm bar spacing Nordmøre grids in a twin-trawl (paired) configuration against the traditional 22 mm bar spacing grid. Size selectivity analyses showed that the 17 and 15 mm grids resulted in no significant reduction in shrimp catch across all length classes. The 17 mm grid significantly reduced redfish bycatch for all length classes and the 15 mm grid significantly reduced redfish bycatch for individuals larger than 95 mm total length. Less redfish entered the codend with the experimental grids, however, the overlap in width between redfish and Northern shrimp limits the overall sorting efficiency of the grids, leaving some redfish still vulnerable to capture.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".