Simulating nonstationary and non‐Gaussian vector ground motions with time‐ and frequency‐dependent lagged coherence
Bibliographic record
Abstract
Abstract Seismic ground motions at multiple sites are nonstationary and non‐Gaussian with potentially time‐ and frequency‐dependent coherence, although the nonstationarity or non‐Gaussian or time‐dependent coherence aspects are often neglected because of lack of algorithm or method to take all these aspects into account to simulate synthetic ground motion records at multiple sites. In the present study, an iterative power and amplitude correction algorithm is proposed to simulate the nonstationary and non‐Gaussian vector process and takes into account time‐ and frequency‐dependent coherence. The algorithm usually converges within 10 iterations. It can be viewed as the extension of the well‐known iterative amplitude adjust Fourier transform algorithm for generating a vector of surrogates. The proposed algorithm uses the S‐transform and discrete orthonormal S‐transform rather than the ordinary Fourier transform. The adequacy of the proposed algorithm is validated numerically by using simulated ground motions.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".