Evaluating Chinook salmon (<i>Oncorhynchus tshawytscha</i>) response to artificial light in support of bycatch mitigation
Bibliographic record
Abstract
In commercial trawl fisheries in the North Pacific and US West Coast, fishermen and scientists are evaluating if artificial lights facilitate escapement of bycaught Chinook salmon (Oncorhynchus tshawytscha) from the trawl by attracting them to an opening provided by a bycatch reduction device. Inconsistent behaviour and escapement rates when lights were used in the trawl led us to conduct a laboratory study to evaluate the role of light properties (intensity, colour, and strobe) on marine Chinook salmon behaviour. Results from this study suggest a negative phototactic response. Light colour and strobe, and the interaction between them, differentially affected behavioural response with regard to mean swimming speed and distance from and habituation to the light. White light intensity had limited influence on response; however, the range of trialed intensities was limited. While behaviour is contextual and responses in a laboratory setting cannot be directly extrapolated to responses in fishing gear, this study highlights the significant role of light properties when trying to affect behaviour for bycatch mitigation and the importance of distinguishing between a response to light and to illuminated surroundings.
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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 | 0.000 | 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".