Improving the Nordmøre-grid system with an aft open top panel bycatch reduction device for juvenile redfish exclusion in shrimp trawls
Bibliographic record
Abstract
Shrimp-trawl fisheries often face challenges with bycatch, particularly of juvenile fish species, which can have significant ecological and economic implications. This study evaluated the effectiveness of a low-cost, simple, and innovative open top panel behavioural bycatch reduction device (BRD), positioned aft of the Nordmøre-grid, to reduce juvenile redfish ( Sebastes spp . ) bycatch while maintaining northern shrimp ( Pandalus borealis ) catches. Comparative fishing trials were conducted using a twin-trawl setup to compare the experimental trawl against a traditional shrimp trawl. Results demonstrated a significant 54 % reduction in juvenile redfish bycatch for the open top panel trawl, and it consistently retained fewer redfish across all size classes. Underwater video footage revealed that redfish actively swam out of the BRD, leveraging turbulent water behind the Nordmøre-grid. The experimental trawl also introduced minor length-dependent selectivity for shrimp, but maintained similar size frequency distributions and catch rates, showing a non-significant 4.7 % increase in shrimp retention. This study underscores the potential of simple, low-cost behavioural BRDs to address operational challenges in Canadian northern shrimp fisheries.
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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) | 0.001 | 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 | 0.001 | 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".