Performance assessment and prioritization of mitigation approaches for pre-seismic code structures
Bibliographic record
Abstract
The selection of an efficient mitigation technique from a number of alternatives to reduce the seismic risk of pre-seismic code school buildings is the main focus of this study. An on-ground survey of the school building stock in a large study area that extends for 6000 km 2 enabled the selection of four different benchmark structures. Detailed simulation models are developed for the selected benchmark buildings and 14 retrofit alternatives to define their performance criteria and assess their seismic vulnerability. The earthquake hazard of the study region is accounted for using a wide range of ground motions, representing two seismic scenarios pertinent to several medium seismicity regions. The relative seismic performance of pre-code buildings and different mitigation alternatives from a large number of dynamic response simulations up to collapse is described in terms of fragility curves as well as a proposed measure of response termed the overall performance factor. This measure of response along with the systematic seismic assessment approach adopted in this study enable prioritizing different retrofit alternatives based on their performance-to-cost ratios, which help to arrive at an efficient and cost-effective mitigation strategy for the implementation at the regional scale.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".