Prediction of interaction between a side overflow and bed-load transport in a channel with semi-empirical approaches
Bibliographic record
Abstract
Side weirs are free overflow regulation and diversion structures commonly encountered in flood protection engineering. The lateral loss of water reduces the bed-load transport capacity in the main channel, leading to local sediment deposition near the side overflow. As a consequence, the design overflow is increased in an uncontrolled way. Since this flow–sediment interaction in such a channel has not been studied so far, systematic flume experiments have been performed. Based on these experiments, a two-dimensional empirical model to describe the longitudinal evolution of the aggraded channel reach near the weir has been developed. In addition, a simple and straightforward approach for direct estimation of the side overflow in presence of bed-load transport has been established. To be generally applicable in engineering practice, all input variables are expressed in terms of dimensionless parameters. Finally, the application of the models is demonstrated in a case study on the Rhone River in Switzerland.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".