Simulated instream restoration structures offer smallmouth bass (<i>Micropterus dolomieu</i>) swimming and energetic advantages at high flow velocities
Bibliographic record
Abstract
Restoration practices aimed at fish habitat enhancement often include installation of instream structures. However, mixed outcomes have been reported regarding structure effectiveness, while mechanisms underlying success remain unclear. The interactions between fish and flow conditions generated by instream structures and their subsequent impact on fish energetics may provide some insight. This study seeks to quantify how restoration structures, simulated by cylinders in three orientations, alter the energetics and swimming stability of smallmouth bass (Micropterus dolomieu). Accelerometers measured swimming stability while a respirometer measured energy expenditure at multiple velocities. Particle image velocimetry was used to characterize flow fields behind structures. Structures generated flow conditions that benefited fish energetically. Fish had a smoother gait and expended less energy when swimming near a structure, regardless of its orientation. Benefits varied with flow conditions; reductions in energy expenditure were especially apparent at high flow velocities. Results suggest that restoration structures may be most energetically beneficial in stream systems with consistently high velocities and inform restoration by indicating flow conditions in which structures provide the greatest energetic benefits for fish.
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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".