KAIST1, KAIST2 - KAIST Experiments, in PRJ-1843: LEAP-UCD-2017
Bibliographic record
Abstract
Twenty-four centrifuge model tests of liquefaction and lateral spreading, performed as part of a round robin test program, are shared and compared in this archive. Please see the general report section of the published project for an overview comparison and background of all of the experiments. One document in the report (with “ReadMe” in the file name) describes the organization of the data archive. The comparisons presented in the general report section will serve as an index to help the users find individual experiments of interest. This data from 24 model tests is published as nine separate experiments in this archive (one experiment per centrifuge facility). Each "experiment" includes two or three model tests and each model test includes between one and three destructive shaking events. All of the tests modeled a 4 m thick deposit of Ottawa F-65 sand with a 5-degree surface slope in a rigid box. The tests covered a range of ground motion intensities and a range of relative densities to define the median response and the sensitivity of the response to relative density and shaking intensity. The nine centrifuge facilities involved in this test program included Cambridge University (UK), Ehime University (Japan), IFSTTAR (France), NCU (Taiwan), KAIST (Korea), Kyoto University (Japan), RPI (USA), UC Davis (USA), and Zhejiang University (China).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 |
| Meta-epidemiology (narrow) | 0.006 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.006 | 0.003 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.030 | 0.094 |
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".