Evaluation of a topless bottom-trawl design for fish capture in the summer flounder fishery
Bibliographic record
Abstract
One of the major threats to sea turtles is the incidental capture as bycatch in marine commercial trawl fisheries. A gear-based approach has been suggested to reduce sea turtle bycatch levels in the summer flounder fishery (Paralicthys dentatus). Previous conservation experiments using a turtle excluder device (TED) in the summer flounder fishery resulted in a significant loss of the target species summer flounder, about 35% on average. A topless-trawl design was proposed as an alternative gear design to mitigate sea turtle bycatch. Previous testing showed that a topless-trawl with a headrope length of 48.7 m (160 ft) was effective at reducing sea turtle catch, but had a significant loss of target species, ranging from 51–74% on average, compared to a traditional trawl net with a 19.8-m (65-ft) headrope. In an effort to improve performance of the experimental trawl, a model of the 48.7-m (160-ft) headrope trawl was evaluated at the flume tank at the Memorial University in St. John’s, Newfoundland. This experimental net was optimally reconfigured with thirty 20-cm (8-in) plastic floats on the headrope and two restrictor lines. The 48.7-m (160-ft) topless-trawl with 30 floats and two restrictor lines was tested in the summer flounder fishery in the summer of 2013 to assess its ability to catch summer flounder with two different float configurations. With the optimal float arrangement, the 48.7-m (160-ft) headrope topless-trawl with two restrictor lines had a significant loss of target species (p=0.008), with 22.7% loss compared to a traditional trawl. With this same float arrangement, the topless-trawl had a 12% loss of skate species (the majority of the catch) with no significance from zero (p=0.057). The experimental topless-trawl reduced the capture of all species overall, including the target species, summer flounder.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".