Seismic Response of Liquefiable Sloping Ground: Validation of Class B Predictions against the LEAP Centrifuge Tests
Bibliographic record
Abstract
Numerical predictions of the liquefaction experiments and analysis project (LEAP) centrifuge tests were revisited in order to evaluate the consistency of the numerical approach and the degree of agreement between numerical predictions and recordings for each facility. The calibration of the numerical model is examined against three Ottawa Sand laboratory data sets, and the validity of the original calibration is confirmed. The recordings of the centrifuge experiments for each facility are compared to the corresponding numerical model analysis and results are presented in terms of excess pore pressure time histories and spectral accelerations. The comparison shows that the numerical model, within the range of uncertainties involved, can satisfactorily predict the results of the experiment for most facilities, but experimental challenges of the experiments for few facilities result to an inconsistent agreement. Additional research is required to identify the underlying causes for the discrepancies but the project is deemed an overall success in yielding high-quality testing results, providing insights for future tests, and demonstrating the predictive capabilities of the numerical approach followed.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".