A time‐frequency dependent coherence model for seismic ground motions
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract There are several well‐known empirical lagged spatial coherence models for seismic ground motions proposed in the literature. The models are often developed based on the ordinary Fourier transform. None of the parametric models depend on time and frequency. The present study is focused on the development of the time‐frequency dependent (TF‐dependent) lagged coherence model for the seismic ground motions. The estimation of the TF‐dependent lagged coherence is carried out using the records obtained from dense arrays in Taiwan by applying the S‐transform—a TF‐dependent windowed Fourier transform. The spectral analysis results show that the TF‐dependent lagged coherence decreases with increasing separation or increasing frequency. Most importantly, it is shown that the TF‐dependent lagged coherence varies with the time‐varying intensity within the duration of the records; a higher normalized intensity corresponds to a higher lagged coherence. This feature is included in the developed empirical parametric TF‐dependent lagged coherence model, which is a function of the frequency, the separation between recording sites, and the normalized intensity. A numerical example illustrating its application to simulate nonstationary ground motions at multiple points is presented by using the time‐frequency spectral representation method that was developed based on the S‐transform and discrete orthonormal S‐transform.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 | 0.000 | 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