Risk‐Based Seismic Evaluation of Reinforced Concrete Buildings
Bibliographic record
Abstract
Seismic resiliency of new buildings has improved over the years due to improved seismic codes and design practices. However, vulnerability of seismically deficient older buildings, designed and built on the basis of older codes of practices, poses a significant threat to life safety and survivability of buildings. It is economically not feasible to retrofit the entire inventory of seismically deficient buildings. Therefore, there is need for a comprehensive plan to identify critical buildings and prioritize their retrofit and upgrading requirements. A risk‐based evaluation technique is proposed in this paper to quantify seismic assessment and develop a ranking scheme for reinforced concrete buildings. The seismic hazard, building vulnerability and consequence of failure are handled in hierarchical structures. Some of the input risk parameters, expressed as qualitative and quantitative quantifiers, are transformed into commensurable values. A knowledge‐based fuzzy rule base modelling is developed and verified through the use of 1994 Northridge Earthquake data on seismic damage of reinforced concrete buildings.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".