Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The LEAP-2015 project was the planning phase of the Liquefaction Experiments and Analysis Projects (LEAP). As part of this project, a numerical simulation exercise was organized to assess the predictive capabilities of a number of constitutive models and numerical techniques for modeling of soil liquefaction and lateral spreading of mildly sloping grounds. The dataset presented here documents a series of soil characterization and element tests performed by researchers at the George Washington University for the LEAP-GWU-2015 project. The results of standard soil characterization tests (particle size distribution analysis, specific gravity, minimum and maximum densities, hydraulic conductivity) as well a series of monotonic and cyclic triaxial tests (strain-controlled and stress controlled) on Ottawa F65 sand are shared in this archive. All this data were provided to the LEAP-2015 numerical simulation teams to calibrate the constitutive models used in the numerical simulations.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.045 |
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 it