Parametric Study of Rainfall-Induced Instability in Fine-Grained Sandy Soil
Bibliographic record
Abstract
This study investigates the stability of fine-grained sandy soil slopes under varying rainfall intensities, durations, and geotechnical properties using a parametric analysis within GeoStudio. A total of 4416 unique parameter combinations were analyzed, incorporating variations in unit weight, cohesion, friction angle, slope inclination, slope height, rainfall intensity, and duration. Results reveal that rainfall intensity is the most influential variable on the factor of safety (FS), with higher intensities (e.g., 360 mm/h) on steeper slopes (e.g., 45°) leading to critical FS values below 1, indicating an imminent risk of failure. Under moderate conditions (e.g., 9 mm/h rainfall on slopes of 26.6°), the FS remains above 2. This dataset provides a valuable foundation for training machine learning models to predict slope stability under diverse environmental conditions, contributing to the development of early warning systems for rainfall-induced 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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".