De nouvelles approches pour quantifier le risque de rupture d'une retenue d'eau
Bibliographic record
Abstract
Construction of dams on streams allows multiple beneficial uses to the population. But in the advent of extreme floods, the structures may fail and free the stored water. Recently built structures respond to more and more demanding design standards. Older structures, which were deemed safe at the time of their construction, might sometimes no longer satisfy these new standards. To evaluate the necessity, the importance and the urgency of works that would make these structures conform again, one of the more and more used approaches consists in resorting to a risk analysis. A risk analysis has been applied a posteriori on a site where a failure was observed in order to determine whether this approach would have brought the managers to undertake corrective works. This application shows the limited capacity of the conventional risk analysis for dams. Two alternative approaches are presented and discussed as a tool to evaluate the risk of a site.Key words: risk analysis, dam break, dam, public safety.[Journal translation]
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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 | 0.011 | 0.043 |
| Meta-epidemiology (narrow) | 0.005 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.009 | 0.005 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.005 |
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".