Hydrodynamics of Juvenile Salmon Passage in Sloped-Baffle Culverts
Bibliographic record
Abstract
Recent evidence suggests that, although their ultimate destination is the sea, juvenile salmonids also travel upstream to locate more desirable habitat and feeding areas. Since many culverts are impassible to juvenile salmonids, baffle systems are being evaluated that will facilitate greater upstream passage. A culvert test bed facility at Washington Department of Fish and Wildlife Skookumchuck Rearing Facility near Tenino, Washington was built to test fish passage success and study the hydrodynamic regimes induced by the baffles. The study involved installing baffles within a 40 foot long, 6 foot diameter corrugated culvert and recording 3-D velocities using an Acoustic Doppler Velocimeter (ADV). The purpose of these tests is to describe the hydrodynamics of the baffle flow and to evaluate how different hydraulic conditions may benefit or hinder fish passage. Baffle generated flow structures such as a jet on the low side of the baffle or a roller wave are identified. Using the 3-D velocity data and surface images, the flow structures are then characterized according to their intensity and size. A scaling equation is analyzed to relate the modification of flow features to the independent study parameters. This paper establishes hydraulic guidance that can help biologists and engineers to improve baffle design and configuration to aid juvenile salmon migration.
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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".