and Aftershock Sequence: Constraints on Earthquake Source Parameters and Fault Geometry
Bibliographic record
Abstract
mic zone and was felt by more people than any other earthquake in United States history. The U.S. Geological Survey (USGS) received 148,638 felt reports from 31 states and 4 Canadian provinces. The USGS PAGER system estimates as many as 120,000 people were exposed to shaking intensity levels of IV and greater, with approximately 10,000 exposed to shaking as high as intensity VIII. Both regional and teleseismic moment tensor solutions characterize the earthquake as a northeast-striking reverse fault that nucleated at a depth of approximately 7 2 km. The distri-bution of reported macroseismic intensities is roughly ten times the area of a similarly sized earthquake in the western United States (Horton and Williams, 2012). Near-source and far-field damage reports, which extend as far away as Washington, D.C., (135 km away) and Baltimore, Maryland, (200 km away) are consistent with an earthquake of this size and depth in the eastern United States (EUS). Within the first few days following the earthquake, several government and aca-demic institutions installed 36 portable seismograph stations in the epicentral region, making this among the best-recorded aftershock sequences in the EUS. Based on
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".