Wedge Slope Failure of Natural Sedimentary Rock Formation Based on Weathering Potential
Bibliographic record
Abstract
Weathering and durability play important roles in the instability condition of sedimentary rock formation.Weathering and durability are not only quite dependent on the other characteristics of unweathered sedimentary but also the interbedded sequence of shear strength with the other rock types.This study aims to evaluate the potential failure of sedimentary rock slopes in Batu City, Indonesia, by analyzing weathering and durability characteristics.Slope stability analysis uses a kinematical approach because this approach considers the equilibrium of forces acting on all rigid blocks as in the traditional slice methods.The stereography graphical model in the kinematic analysis showed probable slope sliding potential due to the wedge failure during the rainy season.Laboratory physical properties classified the sedimentary rock layers as lapilli tuff breccia, breccia claystone, tuff claystone, and breccia.Mechanical strength properties produced compression stress between 2.5 to 13.2 MPa.The result shows that the factor of safety (FS) obtained at 1.25 can be classified as a level of susceptibility and an infeasible condition.Generally, a large safety factor value of 1.50 can be assumed for permanent rock slopes.Shear strength behaviour indicated many influences of weathering and durability factors and could be included in low to high strength levels.
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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 | 0.000 |
| 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".