LEAP-ASIA-2019 Simulation Exercise: Comparison of the Type-B and Type-C Numerical Simulations with Centrifuge Test Results
Bibliographic record
Abstract
Abstract This chapter presents a summary of Type-B and Type-C numerical simulations submitted by nine numerical simulation teams that participated in the LEAP-ASIA-2019 prediction campaign, with the results of a selected set of centrifuge model tests on the seismic behavior of a uniform-density, 20-m-long, and 5-degree sandy slope. Time histories of response accelerations, excess pore water pressures, and lateral displacements at the ground surface are compared to the experimental results. A majority of Type-B and Type-C numerical simulations were capable of simulating well the experimental trends observed in the centrifuge tests; in particular, Type-C simulations were found to capture the measured responses more accurately by adjusting the model parameters. Although it is quite challenging to perfectly capture all measured responses (e.g., accelerations, pore pressures, and displacements), the simulation exercises demonstrate that the numerical simulations can be further improved by accumulating high-quality experimental results as a database.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".