A stochastic spatial modeling approach for pit slope stability analysis using 3D limit equilibrium analysis
Bibliographic record
Abstract
This paper presents a stochastic spatial modelling approach to evaluate the stability analysis of a pit slope in an open pit mine in Canada. More than 200 km of geotechnical borehole data drilled and logged in the mine area was used to develop 3D block models of Rock Mass Rating (RMR) and Uniaxial Compressive Strength (UCS), using stochastic Sequential Gaussian Simulation (SGS) method. The pit design was then excavated into the 3D RMR block models. The block models of the geotechnical attributes (UCS and RMR) were then embedded as input into discretized 3D limit equilibrium models created in SLIDE 3D to conduct a stochastic stability analysis of the pit slope. The modeling results were used to investigate possibilities for optimization of the pit slope design.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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".