Rensselaer Polytechnic Institute Centrifuge Experiments of the Seismic Interaction of a Liquefiable Soil with a Cantilever Retaining Wall
Bibliographic record
Abstract
The Liquefaction Experiments and Analysis Projects (LEAP) is an international collaboration to develop a databank of high-quality centrifuge experimental data and to use this data in calibration and validation of numerical tools of soil liquefaction and associated consequences. LEAP-2020 investigated the performance and seismic interaction of a liquefiable (Ottawa sand) soil with a cantilever retaining wall. A total of twenty-three centrifuge model tests were performed at eight centrifuge facilities, as part of a round robin testing program. The experimental results of these tests are published and shared in this archive as eight separate experiments (one experiment per centrifuge facility). Each “experiment” includes a number of tests and each model test includes one or multiple destructive input excitations. The conducted tests cover a broad range of soil relative densities and input motion conditions. These tests provide valuable information on the trends and sensitivity of the soil-retaining wall response to variations in shaking intensity and soil relative density. The eight centrifuge facilities involved in LEAP-2020 program included Ehime University (Japan), KAIST (Korea), Kyoto University (Japan), National Central University (Taiwan), Rensselaer Polytechnic Institute (USA), University of California Davis (USA), University of Cambridge (UK), and Zhejiang University (China). The “Experimental Data Archive Overview” document provides an outline of the associated organization.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.020 | 0.036 |
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".