Les prévisions des brèches de rupture des barrages en terre restent difficiles
Bibliographic record
Abstract
The validity of dam failure studies is based on the appropriateness of the expected failure mode. Failures of earth-fill structures show the importance of the choice of breach parameters for failure evaluation and consequences. This paper summarizes the state of the possibilities for forecasting the breach and the resulting hydrograph in the downstream valley. It describes the most current methods, applies them on a failure case observed in the Saguenay region, Province of Québec, and compares the results. Considering the large uncertainty margin on the results, the paper allows one to understand why breach forecasting must not, in the current state of knowledge, be part of the safety study process, and that it is preferable to stay with a definition for breach based on a rule intelligently applied with respect to the case, the structure, and its composition.Key words: dam failure, dam breach, erosion, forecasting, flood of failure, earth-fill dam.[Journal translation]
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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 | 0.001 |
| 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".