Projecting Sets of Ground-Motion Models and Their Use to Evaluate Seismic Hazard and Uniform Hazard Spectrum for Mainland China
Why this work is in the frame
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Bibliographic record
Abstract
A projection method was used to develop ground-motion models (GMMs) to predict the peak ground accelerations (PGAs) that are used to assess the fourth and fifth generations of Chinese seismic hazard maps. In the present study, the projection method was applied to develop sets of projected GMMs to predict PGAs and spectral accelerations (SAs) that are applicable to different seismic regions in Mainland China. The projected GMMs were based on the GMMs from Next Generation Attenuation Relationships for Western US. It is shown that the projected GMMs differ slightly from their corresponding original versions and that the predicted median PGA values by the projected GMMs represent the instrumental ground-motion data well. These newly projected sets of GMMs were used to estimate the seismic hazard map and uniform hazard spectrum (UHS) for Mainland China. For the estimation, smoothed seismic source models and spatially varying magnitude-recurrence relations were developed based on historical earthquake catalog and completeness analysis. The results indicate that, in general, the estimated seismic hazard agrees with that reported in the fifth-generation Chinese seismic hazard map. However, large discrepancies were also observed for a few locations. These discrepancies are partly attributed to how the large historical earthquake events are spatially smoothed. In addition, it was observed that the estimated shape of the UHS for regions with a significant seismic hazard is relatively consistent but differs from the standardized seismic design spectrum recommended in the Chinese design code.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it