Behavioral responses of sea lamprey (<i>Petromyzon marinus</i>) and white sucker (<i>Catostomus commersonii</i>) to turbulent flow during fishway passage attempts
Bibliographic record
Abstract
An understanding of how undesirable and desirable fish species respond behaviorally to turbulent flow in fishways would guide development of selective fish passage techniques. We applied high-resolution computational fluid dynamics modeling and competing risks analysis towards the development of predictive selective passage models. Sea lamprey (Petromyzon marinus; an invasive fish in the Great Lakes Basin, North America) upstream passage probability declined from 0.73 to 0.03 as flow conditions became increasingly turbulent, while declines in white sucker (Catostomus commersonii, a native fish in the region) upstream passage probability were less substantial (0.53 to 0.44). Deploying a sea lamprey trap in the fishway did not effectively reduce sea lamprey upstream passage probability, though capture rate increased during trials with cooler water temperature and low total kinetic energy. Bifurcated fishways that maintain low turbulent flow in the entrapment route and high turbulent flow in the upstream passage route could increase the effectiveness of trapping sea lamprey in fishways as a means to advance selective passage goals.
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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".