The effect of Nordmøre grid length and angle on codend entry of bycatch fish species and shrimp catches
Bibliographic record
Abstract
The Nordmøre grid is regarded as an efficient bycatch-reducing device and is used in various shrimp trawl fisheries globally. However, in some shrimp fisheries, bycatch remains a problem that seriously impacts commercial trawl activities. This study tested and compared the performance of two versions of the Nordmøre grid in the northeast Arctic deepwater (northern) shrimp (Pandalus borealis) fishery, a standard version with an operating angle of approximately 45° and a longer version of the grid (40% longer) with an operating angle of approximately 30°. The grid passage probability for the bycatch of juvenile cod (Gadus morhua), haddock (Melanogrammus aeglefinus), American plaice (Hippoglossoides platessoides), and redfish (Sebastes spp.) increased significantly for certain size ranges of fish when using the longer grid. The longer grid also resulted in a significant increase in grid passage probability for large shrimp. Previous studies have reported that a reduced operating angle can lead to a lower grid passage probability for bycatch fish species and shrimp; however, the results of the current study demonstrate that a longer Nordmøre grid more than compensates for the reduced operational angle.
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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 | 0.005 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 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".