Simulation Data for "Community-Driven Code Comparisons for Three-Dimensional Dynamic Modeling of Sequences of Earthquakes and Aseismic Slip"
Bibliographic record
Abstract
Simulation data from Jiang et al. (2022), "Community-Driven Code Comparisons for Three-Dimensional Dynamic Modeling of Sequences of Earthquakes and Aseismic Slip," Journal of Geophysical Research: Solid Earth. The archive includes simulation data for 3D SEAS benchmarks BP4-QD and BP5-QD that are analyzed in our paper (descriptions in NOTES.txt) BP4-QD Benchmark Simulations:1000 m: jiang.5, lambert.8, barbot.3, barbot.2, dliu.2, li.4500 m: jiang.3, lambert.3, barbot.5, barbot.7, ozawa BP5-QD Benchmark Simulations:2000 m: jiang.6, lambert.8, liu.4, cattania.5, dli.7, barbot.3, dliu.10, li.31000 m: jiang.2, lambert.7, liu.5, cattania.3, ozawa, dli.5, barbot, dliu.6, li.2500 m: jiang.4, lambert.9, liu.6, cattania.4, ozawa.2, dli.6, barbot.2, dliu.8250 m: lambert.10, liu.7 BP5-QD with Off-Fault Data:1000 m: lambert.7, dli.5, barbot, dliu.6, li.2500 m: lambert.9, dli.6, barbot.2, dliu.8 Tables 2–4 in our paper summarizes details of numerical codes and selected simulations. The benchmark descriptions and the full suite of simulation data are available at SEAS online platform https://strike.scec.org/cvws/seas/.
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 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 teacher head, 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".