GIS-based assessment of bedding-controlled planar failure potential at Canada Hill in Miri, Sarawak, Malaysia
Bibliographic record
Abstract
Planar failure occurrences are prevalent in Canada Hill during prolonged periods of heavy rainfall. The incidences of planar failures in the study area are less frequent than other types of failures, but it is the most destructive. It is critical to understand the geological structures that contribute to landslide occurrences in the sedimentary rock slopes to improve the assessment of landslide susceptibility. Planar failure occurs when a structural discontinuity plane daylight towards the slope at a gentler angle than the slope angle but greater than the friction angle of the discontinuity plane. The geometrical relationship between the bedding attitude and the slope topography was used to evaluate potential planar failures. This study used the method of interpolating direction cosine data to spatially distribute the bedding plane information across the study area from irregularly distributed bedding measurements. This was assessed with LiDAR-derived DEM in a geographic information system (GIS) platform to determine slopes with various levels of potential for planar failures. Slopes that face northwest at the northwestern section of Canada Hill has the highest potential for planar failures. This suggests a high conformity between the slopes and the bedding attitude. The potential of planar failure is lower for slopes facing the east. This method provides a significant indication of the zones that are potential to planar failures across Canada Hill which can be used as one of the key components in future landslide susceptibility assessments. In addition, this method can be applied for landscape-scale modelling applications in regions with simple geological structures.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".