A Hazard and Risk Management System for Large Rock Slope Hazards Affecting Pipelines in Mountainous Terrain
Bibliographic record
Abstract
Pipelines and other linear facilities that traverse mountainous terrain may be subject to rock fall and rock slide hazards. A system is required to determine which sites pose the greatest hazard to the facility. Once sites are ranked according to hazard exposure, a risk management program involving inspection, monitoring, contingency planning and/or mitigation can be implemented in a systematic and defensible manner. A hazard rating methodology was developed to identify and characterize rock slope hazards above a South American Concentrate Pipeline, and to provide a relative ranking of hazard exposure for the pipeline, an access road and operational personnel. The rating methodology incorporates the geometry of the right-of-way, estimated pipe depth, staff and vehicle occupancy time, failure mechanism and magnitude, and the annual probability of hazard occurrence. This information is used in a risk-based framework to assign relative hazard ratings within rock slope sections of relatively uniform hazard exposure. This paper outlines a general framework for natural hazard and risk management along linear facilities, describes the rock slope hazard rating methodology, and illustrates how the system was applied along a South American Concentrate Pipeline.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".