Shallow Landslide Model of Granite Residual Soil Considering Shearing Dilation Effect and Seepage Force
Bibliographic record
Abstract
The granite residual soil slopes in southeast Guangxi, China, occur failures and cause frequent landslides under rainfall conditions. Shallow landslides are the main failure mode. Shearing dilation effect and groundwater seepage both exist within the landslide movement. The movement characteristic is the scientific basis of landslide prevention and warning. In this study, a shallow landslide model of granite residual soil is established to reflect the coexistence of shearing dilation effect and groundwater seepage. The results include three aspects. (1) Groundwater seepage along the slope can lead to the increase of the sliding force, which is not conducive to slope stability. (2) Dilation promotes the formation of negative excess pore pressure, which can counteract the increase in static pore pressure caused by rain infiltration. It has a certain inhibitive effect on landslide motion. Such restriction weakens with the decrease of dilation angle and enhances with the increase of dilation angle. (3) Contraction can prompt the positive excess pore water pressure to increase rapidly to the limit of liquefaction in a short period of time. The research results will provide a theoretical basis for the prevention and warning of rainfall-induced granite residual soil landslide in southeast Guangxi.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".