Mortality and injury assessment for three species of fish exposed to simulated turbine blade strike
Bibliographic record
Abstract
Injury and mortality of fish during downstream passage through hydropower turbines is among the leading direct impacts of hydropower. Understanding the relationships among various strike variables and injury and mortality rates are necessary for improvements in turbine design. We subjected three species of fish to simulated blade strike in laboratory studies with different blade thicknesses, impact velocities, and body orientations to develop relationships between these variables and probability of injury and mortality. Midbody strikes resulted in higher mortality than head strikes, and tail strikes produced the least mortality. Lateral strikes caused more mortality than dorsal and ventral strikes, and higher strike velocities and thinner blades contributed to increased mortality. Several injury types were significantly associated with increased mortality, including injuries to the operculum, gills, viscera, heart, liver, swim bladder, muscle, and bone fractures. Results from this study will be used to define biologically based design criteria that can be used by turbine designers to improve designs (e.g., increased leading-edge thickness and slower turbine speeds) to minimize the probability and impact of blade strike.
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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 | 0.001 | 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".