Site‐Effects Model for Central and Eastern North America Based on Peak Frequency
Bibliographic record
Abstract
Abstract We develop a regional site‐effects model for central and eastern North America based on an analysis of the residuals of observed ground‐motion parameters relative to two regional ground‐motion prediction equations: one model has a hard‐rock (site class A) reference site condition, whereas the other is referenced to a B/C boundary site condition (site classification of National Earthquake Hazard Reduction Program). In both cases, the residuals are well described by a site‐effects model based on site fundamental frequency f peak , in which f peak is as determined from the horizontal‐to‐vertical component response spectral ratios. Accordingly, we derive an f peak ‐based site amplification model with respect to B/C and hard‐rock reference site conditions. Implementing the f peak ‐based model, we reduce random variability in amplitudes σ by 10% on average, for a selected database from the Next Generation Attenuation‐East Project, relative to the value obtained when using a generic site‐effects model parameterized by near‐surface shear‐wave velocity (time‐averaged shear‐wave velocity in the upper 30 m, V S 30 ). The reduction in σ comes from the site‐to‐site component of the variability (reduced by 20% on average), whereas the single‐station variability is unaffected.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".