Comparison of Nonlinear Structural Responses for Accelerograms Simulated from the Stochastic Finite-Fault Approach versus the Hybrid Broadband Approach
Bibliographic record
Abstract
Abstract We compare nonlinear structural responses for simulated accelerograms generated based on two widely used methods: the stochastic finite-fault (SFF) approach and the hybrid broadband (HBB) approach. In this study, nonlinear response potential is characterized by the peak ductility demand of inelastic single-degree-of-freedom (SDOF) systems. The key question to be addressed is this: for the same earthquake scenario, is the nonlinear response potential due to stochastic finite-fault records similar to the nonlinear response potential due to hybrid broadband records? We conclude that the peak nonlinear response characteristics of accelerograms generated using the two methods are similar, if both sets of records have the same median and the same variability. If only the median elastic response spectra of record sets from the two methods are the same, the hybrid broadband records may produce greater peak nonlinear responses due to their tendency to feature greater record-to-record variability in the low-frequency range.
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How this classification was reachedexpand
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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".