Survival of fish passing downstream at a small hydropower facility
Bibliographic record
Abstract
Hydropower dams can negatively affect upstream and downstream migratory fish populations in many ways, such as blocking access to upstream habitats and causing injuries or mortality during downstream passage. For downstream passage at projects in the USA, federal regulators and agencies responsible for oversight of hydropower facilities typically require assessment studies and mitigation to address negative effects, with a primary goal of minimising fish impingement and turbine entrainment and mortality. So as to assess the effects of downstream passage of fish populations at a unique, small hydro project on the Mississippi River, impingement and entrainment rates, Oberymeyer gate passage, spillway gate passage, turbine survival, and total downstream passage survival were estimated. It was determined that 85% of fish passing downstream at the project would be small enough to pass through the bar spacing of the trash racks and 15% would be physically excluded. When 55% of river flow enters the turbine intake channel, the total project survival rates were estimated to be 77.3% with an Obermeyer gate bypass rate of 10 and 96.6% with a gate bypass rate of 90%. Therefore, any effects on local fish populations resulting from the operation of the project are expected to be negligible and inconsequential on the basis of expected survival rates for the range and probability of river flows occurring at the project.
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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) | 0.002 | 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".