Two-dimensional hydraulic-habitat modeling of a rehabilitated river
Bibliographic record
Abstract
The application of a 2D hydraulic-habitat model, River2D, to simulate flows and fish habitat areas in a reach of the Nicolet River (Quebec, Canada) containing two sets of double-wing rock current deflectors to enhance fish habitat was examined. Depth-averaged velocity in the reach was determined using one or two measurement points in the vertical under the assumption that the profile was logarithmic; however, the presence of boulders and obstructions disturbed the profile, making it difficult to characterize using only two measurement points. The sensitivity of the simulation results to roughness characterization, topographic scale, mesh refinement, and boundary conditions was evaluated. The simulated and observed depths had correlation coefficients of 0.93 to 0.97, while the velocity correlation coefficients were 0.56 to 0.67. Qualitatively, the model accurately predicted the flow patterns, e.g. the recirculation zones downstream of the deflectors. Habitat suitability curves for brown trout, taken from literature, were used in the habitat model. Simulated discharges from 0.74 m3/s to 1.94 m3/s were critical minimum flows for suitable spawning brown trout habitat. The model was adequate for qualitatively simulating flow and habitat in this reach, however, the complex flow conditions may be better represented by a 3D model.
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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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".