Improved intensity measures for probabilistic seismic demand analysis. Part 1: development of improved intensity measures
Bibliographic record
Abstract
This is the first of two companion papers on improved intensity measures of strong seismic ground motions for use in probabilistic seismic demand analysis. It describes the formulation and the development of new intensity measures. The second paper illustrates the application of the developed intensity measures in probabilistic seismic demand analysis. The development of the intensity measures was based on investigations of the seismic responses of three reinforced concrete frame buildings (4, 10, and 16-storey high) designed for Vancouver. The buildings were subjected to a selected set of seismic motions scaled to different intensity levels. Maximum interstorey drifts obtained from nonlinear dynamic analyses were used as response parameters. Based on the results from the analyses, two intensity measures are proposed: one for short- and intermediate-period buildings, and another one for long-period buildings. The proposed intensity measures are superior compared to that represented by the spectral acceleration at the fundamental building period (Sa(T1)), which is currently the most widely used intensity measure in probabilistic seismic demand analysis.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".