Can behavioral fish-guidance devices protect juvenile Chinook salmon (<i>Oncorhynchus tshawytscha</i>) from entrainment into unscreened water-diversion pipes?
Bibliographic record
Abstract
Entrainment through water-diversion structures is a major passage challenge for fishes in watersheds worldwide. Behavioral guidance devices may be effective in passing fish by diversion inlets, thereby decreasing entrainment without reducing water-diversion rates, but data on their effectiveness is limited. In California’s central valley, out-migrating Chinook salmon (Oncorhynchus tshawytscha) are a species at risk for entrainment through unscreened, small-scale water-diversion pipes. Therefore, we tested entrainment susceptibility and behavior of juvenile Chinook salmon in a large-river-simulation flume at a “river” velocity of 0.15 m·s–1with a 0.46 m diameter pipe diverting water at 0.57 m3·s–1, during the day and night. Compared with control conditions (no fish deterrent devices present), mean fish entrainment increased by 61% (day) and 43% (night) when underwater strobe lights were active, decreased by 30% when using a metal vibrating (12 Hz) ring during the night, and was unaffected by velocity cap attachments. Fish entrainments started at water velocities of 0.8 m·s–1and decreased by 54% from spring to summer, possibly resulting from decreased pipe-passage frequency and smaller fish-school sizes. Our findings suggest that substantial entrainment can occur if fish repeatedly pass within 1.5 m of active unscreened diversions, with an estimated 50% of fish lost after encountering 18 pipes in spring and 50 pipes in summer.
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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".