Élaboration d’un modèle de simulation des niveaux d’inondation à partir d’un SIG et application à un site : rivière Saint-François à Sherbrooke
Bibliographic record
Abstract
Afin de mieux identifier spatialement les zones les plus à risques pour les populations riveraines et les infrastructures lors de fortes crues, un projet visant l’élaboration et l’application d’un modèle de simulation des niveaux d’inondation à partir d’un Système d’information géographique (SIG) a été mis en place. Ce modèle de simulation intègre, à partir d’un SIG, des données de débits et de niveaux et un modèle numérique d’élévation (MNE) de haute précision, rendant possible la simulation ainsi que la visualisation des différents niveaux atteints par la rivière Saint-François. Les résultats du modèle sont présentés visuellement sous forme de cartes permettant d’observer et d’identifier les limites des nappes d’eau lors des crues ou inondations majeures.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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; both teacher heads agree on what is shown here.
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".