Stability of Rock Slope using Kinematic Analysis: A Case Study at Bukit Gemilang, Sungai Besi, Kuala Lumpur
Bibliographic record
Abstract
Discontinuities are crucial for assessing the stability of rock slopes, with their geometric properties such as direction and orientation serving as key indicators. Conventionally, compasses have been used to measure the direction and orientation of these discontinuities, but this method requires considerable time for data collection. Recent advancements in remote sensing technology, particularly Terrestrial Laser Scanners (TLS), provide a more efficient alternative for measuring rock slope discontinuities. This study focuses on the stability of the rock slope at Bukit Gemilang, located in the Universiti Pertahanan Nasional Malaysia (UPNM) campus in Sungai Besi, Kuala Lumpur. Investigating this area is crucial because of the risks it poses to students and staff who pass by, particularly given the lack of prior studies reported in the literature. The paper aims to determine the orientation of the discontinuity features of the Bukit Gemilang rock slope using both conventional and TLS methods. Statistical tests indicate no significant difference between the data collected from the two methods, suggesting that TLS is a reliable tool for obtaining preliminary information on rock slope stability. This data is then utilized for kinematic analysis using Rocscience Dips software, which indicates low probabilities of planar, wedge, and toppling failures at 16.16%, 7.84%, and 4.04%, respectively. This suggests that the rock slope is considered stable. However, to enhance safety for road users on Bukit Gemilang, it is recommended to consider the installation of dowel bars and wire mesh in certain areas within the fractured rock zone.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".