Testing the application of reliability-based design acceptance criteria (RBDAC) for open pit slopes
Why this work is in the frame
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Bibliographic record
Abstract
Open-pit slope design is increasingly adopting probabilistic approaches. Designs are assessed against design acceptance criteria considering the potential consequences of failure. Mature operations have recognized the importance of optimizing slope configurations by considering design reliability and the potential consequences of slope failure. This parametric study applied quantitative reliability-based design acceptance criteria (RBDAC) to evaluate the factor of safety and probability of failure from probabilistic slope stability analysis for an open-pit slope modified from an actual pit slope in British Columbia, Canada. A matrix of acceptability criteria was used, based on the design reliability and potential economic consequences of failure. The three design reliability levels considered were derived from parameter and geometrical uncertainties by incorporating diverse scenarios, thus reflecting the geotechnical, geological, and hydrogeological characteristics of the implemented pit slope. Other uncertainties include computational simplifications and spatial variability. Results highlight the significant role uncertainty plays in the design process. Using the RBDAC matrix facilitates transparent evaluation of uncertainty, allowing determination and communication of the level of reliability in the design.
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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 it