Probabilistic version of the Robertson and Wride method for liquefaction evaluation: development and application
Bibliographic record
Abstract
The Robertson and Wride method is the most widely used cone penetration test (CPT)-based method for soil liquefaction evaluation. This method is a deterministic model, which expresses liquefaction potential in terms of factor of safety. On many occasions, there is a need to express the liquefaction potential in terms of liquefaction probability. Although several probabilistic models are available in the literature, there is an advantage having a probabilistic version of the Robertson and Wride method so that the engineer who prefers to use this method can obtain additional information of liquefaction probability with minimal extra effort. In this paper, a simple model is developed, which links the factor of safety determined by the Robertson and Wride method to the liquefaction probability. The model, referred to as the probabilistic RW model, is developed, and verified, in a mathematically rigorous manner. Simplified equations for assessing the variation of liquefaction probability caused by the uncertainty in input parameters are also developed. Example applications are presented to demonstrate the developed models.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".