Application of geophysical methods for the investigation of the large gravitational mass movement of Séchilienne, France
Bibliographic record
Abstract
Several geophysical techniques (electromagnetic profiling, electrical tomography, seismic refraction tomography, and spontaneous potential and seismic noise measurement) were applied in the investigation of the large gravitational mass movement of Séchilienne. France. The aim of this study was to test the ability of these methods to characterize and delineate the rock mass affected by this complex movement in mica schists, whose lateral and vertical limits are still uncertain. A major observation of this study is that all the zones strongly deformed (previously and at present) by the movement are characterized by high electrical resistivity values (>3 kΩ·m), in contrast to the undisturbed mass, which exhibits resistivity values between a few hundred and 1 kΩ·m. As shown by the surface observations and the seismic results, this resistivity increase is due to a high degree of fracturing associated with the creation of air-filled voids inside the mass. Other geophysical techniques were tested along a horizontal transect through the movement, and an outstanding coherency appeared between the geophysical anomalies and the displacement rate curve. These preliminary results illustrate the benefits of combined geophysical techniques for characterizing the rock mass involved in the movement. Results also suggest that monitoring the evolution of the rock mass movement with time-lapse geophysical surveys could be beneficial.Key words: gravitational movement, geophysical methods, Séchilienne.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".