NGA‐East ground‐motion characterization model Part II: Implementation and hazard implications
Bibliographic record
Abstract
As a companion article to Goulet et al., we describe implementation of the NGA‐East ground motion characterization (GMC) model in probabilistic seismic hazard analysis (PSHA) for sites in the Central and Eastern United States (CEUS). We present extensions to the EPRI/DOE/NRC seismic source characterization (SSC) model for the CEUS needed for full implementation of NGA‐East. Comparisons are presented to the EPRI GMC, the currently accepted model by the U.S. Nuclear Regulatory Commission for hazard assessment at nuclear facilities. Comparisons are presented both in terms of GMC model components and in the resulting seismic hazard assessments for a range of site locations in the CEUS. Illustrations of the effect of various components of the NGA‐East GMC on seismic hazard results are also presented. Finally, we present recommendations for application of the NGA‐East GMC in PSHA.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".