An update to the strain-based approach to pit wall failure prediction, and a justification for slope monitoring
Bibliographic record
Abstract
Effective management and mitigation of pit slope instability in open pit mines begins with a comprehensive slope monitoring programme. The ability to differentiate between non-critical pit wall movements due to rebound or relaxation of the excavated slopes and movements that may be indicative of slope failure is important for maintaining a safe working environment and maximizing production. Slope failure prediction methods using velocity, acceleration, and strain criteria have been introduced and put into practice over the past few decades. Forty-eight slope failures with surface monitoring data are presented and assessed using the strain-based failure prediction approach, with consideration of the quality of the rock mass and the potential failure mechanism. The results indicate that the strain-based approach can be used to provide general guidance regarding strain thresholds for pit walls for a variety of failure modes in diverse geological environments. The advantages and potential drawbacks of the strain-based and other slope failure prediction methods are discussed. The importance of implementing a pit slope monitoring and performance evaluation system early in mine development is also emphasized.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".