Géographie de l’inondation des marais de la basse-Loire : l’exemple de la crue de l’hiver 2000-2001
Bibliographic record
Abstract
Connaître la géographie de l’inondation des marais de la Basse-Loire (notamment ceux de l’estuaire de la Loire, de la Brière et du lac de Grand-Lieu) est fondamental pour en assurer une gestion adéquate. Cependant, on doit tenir compte des profondes modifications de leur hydrologie par les aménagements hydrauliques réalisés depuis le xviiie siècle. À partir de l’exemple de la dernière grande crue, survenue au cours de l’hiver 2000-2001, l’article montre l’apport de la télédétection spatiale (images des satellites Landsat 7 ETM+ et Spot 4) et aérienne pour délimiter les marais inondés et d’en calculer la surface, en corrélation avec les niveaux d’eau relevés à la même période. Le cas de la commune de Trignac illustre l’intérêt de ce type d’étude pour prévenir les risques liés à l’urbanisation. Une comparaison intersaisonnière et interannuelle révèle l’extension de l’inondation permanente en raison de la multiplication des étangs de chasse.
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 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".