Probabilistic and Deterministic Approach to Assess Liquefaction Potential at Selected Sites Using SPT Data
Bibliographic record
Abstract
In this study, five major sites were assessed across Windsor-Essex Region in the Province of Ontario, Canada, to determine if an earthquake event with the probability of exceedance 2% in 50 years, i.e., a return period of 2,475 years, may lead to liquefaction. The simplified procedure suggested by Idriss and Boulanger was used to determine the liquefaction factor of safety and probability. The cyclic stress ratio (CSR) and cyclic resistance ratio (CRR) are depth functions; assessment was done with respect to depth for at least 3 borelogs per site. Sites were assessed for magnitude 6.0, 7.0, and 8.0 earthquakes. Results show that sites with higher groundwater tables, low N values, and low fine contents are prone to liquefaction, with probabilities ranging from 60% to 100%. The factor of safety in some scenarios was below 0.40. Extensive assessments should be conducted to prevent structural damage and loss of capital and lives.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".