Experimental study on the deformation and failure of a cut slope under rainfall
Bibliographic record
Abstract
On June 11, 2016, a landslide occurred in Miaoling village, Jiujiang city, Jiangxi Province, China, following continuous rainfall. An engineering geological profile indicated that the landslide consisted of a stiff crust of residual Quaternary deposits overlying a water-sensitive gravelly clay layer with a soft-plastic consistency. A geotechnical field investigation and physical models of rainfall-induced landslides were carried out in situ and in the laboratory and included the use of a new sensors to develop a geotechnical model of the cut slope. During the rainfall process in the physical simulation experiments, automatic rainfall, three-dimensional scanning, and multiparameter monitoring were conducted to analyze the resulting landslides. The results showed that the increase in moisture and the generation of pore water pressure led to changes in soil pressure and the development of plastic deformation. An analysis performed after rainfall using a strain-softening behavior model showed the initiation and propagation of plastic zones, as well as the development of landslide cracks close to the observed ones. Therefore, it was proposed that the Miaoling–Jiujiang landslide could be explained by a progressive failure mechanism.
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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 | 0.000 | 0.000 |
| 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".