A Benchmark Slope For System Reliability Analysis
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Bibliographic record
Abstract
In a probabilistic slope stability analysis, the failure probability associated with the most critical slip surface (the one with the minimum reliability index) is known to be smaller than that obtained for the system as a whole where all potential slip surfaces are considered. System slope reliability has been studied in recent years by several probabilistic methods, including the Random Finite Element Method (RFEM), Limit Equilibrium Methods (LEM) combined with First Order Reliability Methods (FORM), and Response Surface Methods (RSM). The only one of these methods that can properly account for spatial variability however is the RFEM. In this paper, we set up a benchmark slope for system reliability analysis and compare the probability of failure obtained both with and without inclusion of spatial variability. The paper will give recommendations for the types of slope reliability problems that benefit from proper consideration of spatial variability.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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