Numerical modelling of river bank migration in a small stream
Bibliographic record
Abstract
Rivers worldwide have undergone various engineering interventions, including dredging, river straightening, and bank stabilization. These measures have led to increased riverbed erosion, habitat loss, diminished flood retention capacity, and deteriorating water quality. One such case study is the Petit-Pot-au-Beurre (PPAB), a second-order stream situated in Saint Robert, Quebec, Canada, which underwent straightening and dredging in the past. Due to its modest size, the PPAB presents an opportunity to experiment with various eco-friendly, cost-effective measures aimed at promoting bank migration. Therefore, the 2D hydrodynamic model Telemac2d, coupled with Gaia, was employed to assess the potential for bank migration development. The findings suggest that the migration of steep banks leads to channel widening, resulting in reduced water depth and shear stress. This reduces the river’s transport capacity, suggesting the need for additional measures like vegetation planting, sediment injection, or deflector installation to sustain ongoing bank 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".