Méthode de localisation des moraines de convergence dans une ancienne vallée glaciaire (Pyrénées, France) : conséquences sur les instabilités des moraines et reconstruction des glaciers au Würm
Bibliographic record
Abstract
In this work, we show how it is possible to locate the thickest of till areas from the geological and geomorphological map-making of glacial formations in high mountain sites. This qualitative information is the result of a mapping methodology realized in two stages, and applied to an old glaciated Pyrenees valley, the Aspe valley. In the first stage, we show the need to draw the map of the undifferentiated glacial formations to establish the geomorphological Aspe valley map during the Würm (10 000 to 70 000 BC). This period of glaciation is correlated to the Northern Europe glacial Weichselien episode. The second stage consists in superimposing the topographic and geomorphological maps to determine the altimetric position of the lateral and convergence tills of the various glaciers. The method proposed makes it possible to obtain on a map, the position of the thickest convergence tills. The thickest of the convergence tills is verified in the field by different electrical surveys. Also, we observed that more than 50% of the landslides present in this valley are probably of Holocene age, but not reactivated at present. This can be explained by the strong variation of their mechanical characteristics compared with the slope of the side and the substratum. We show that the suggested map-making method can be applied, under certain conditions, to other glaciated valleys.Key words: Pyrenees, Würm (Weichselian age), glacial modelling, moraine, landslides.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".