Mechanical state of gravel soil in mobilization of rainfall-induced landslides in the Wenchuan seismic area, Sichuan province, China
Bibliographic record
Abstract
Abstract. Although gravel soils generated by seismic shaking in Wenchuan earthquake area have subjected to natural consolidation process for nearly ten years, geological hazards, such as slope failures with ensuing landslides, frequently are haunting the area. In this paper, artificial flume model tests and triaxial tests were used to make close observation on the mechanical state of gravel soil in Wenchuan seismic area. The results showed that: (1) The timing and patterns of landslide initiations were closely related to their initial dry densities, and the initiation processes were accompanied with a variation of dry density and void ratio; (2) Fine particle migration in soil and coarse-fine particle content rearrangement contributed to the internal micro structure reorganization, which was supposed to be the main reason for variation of dry density and void ratio; (3) Gravel soils with unchanged grain compositions, if under the same hydrostatic compression, they approached to an identical critical void ratio to fail; (4) The mechanical state of certain sort of gravel soil can be identified by its relative position between state parameter (e, p') and ec-p' planar critical state line; (5) Gravel soil slope failed and then evolved into landslide under lasting rainfall leaching, while in gravel slope there co-existed soil dilatation and contraction, but the dilatation was dominant. Above research findings not only could be used to interpret landslide initiation but also would provide an insight for landslide warning forecast of gravel slope in seismic area.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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".