Improving release efficiency of cod (<i>Gadus morhua</i>) and haddock (<i>Melanogrammus aeglefinus</i>) in the Barents Sea demersal trawl fishery by stimulating escape behaviour
Bibliographic record
Abstract
We tested the ability of stimulators to improve the release efficiency of cod (Gadus morhua) and haddock (Melanogrammus aeglefinus) through the meshes of a square mesh section installed in a trawl. The section was tested in three different configurations: without any stimulation device, with a mechanical stimulation device, and with LED light stimulation devices. We analysed and compared the behaviour of cod and haddock in all three configurations based on release results and underwater recordings. Parallel to the fishing trials, we carried out fall-through tests to determine the upper physical size limits for cod and haddock to be able to escape through the square meshes in the section. This enabled us to infer whether lack of release efficiency was due to fish behaviour or release potential of the square meshes in the section. The results showed that the escape behaviour of haddock can be triggered by mechanical stimulation. In contrast, cod did not react significantly to the presence of mechanical stimulators. LED light stimulation had some effect on the behaviour of haddock, but not on cod.
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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 | 0.000 |
| 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) | 0.001 | 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".