Developing a full-scale shaking codend to reduce the capture of small fish
Bibliographic record
Abstract
To reduce the retention of undersized fish in the redfish (Sebastes spp.) trawl fishery in the Gulf of St. Lawrence, Canada, we developed a full-scale shaking codend. The shaking codend uses a mechanical stimulating device, an elliptical-shaped piece of polyvinyl chloride canvas, attached to the posterior of a T90 codend that generates a lifting force with respect to drag, causing a 'shaking motion'. A shaking codend could stimulate fish movement and increase contact probability, both of which could increase the escape of small redfish out of a codend, especially when combined with a codend that maintains mesh openings. The movement and fishing characteristics of a shaking codend (T90 codend with canvas) relative to a T90 codend (without canvas) were tested in a flume tank and field experiment. In the flume tank test, the shaking codend had a peak-to-peak amplitude (i.e. the distance the codend moves from the lowest to highest depth) > 24 cm higher than the T90 codend for each velocity tested (1.0-1.8 kt), higher amplitude ratio, and a higher period (1 revolution) that gradually decreased with increasing velocity. The total acceleration (m s-2) and drag forces (kgf) estimated for the shaking codend were significantly higher than the T90 codend across all flow velocities. The results from the field experiment, considered preliminary due to a small sample size, showed that the shaking codend significantly reduced the capture of small redfish (< 21 cm) and the best fit model did not need to consider contact probability which was necessary for the non-shaking T90 codend. Overall, the dynamics of the movement of the codend was described and could be potentially used as an effective technique to reduce the catch of small redfish, and perhaps in other trawl fisheries to reduce the catch of small fish.
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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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".