Methodology for seismic risk screening of existing buildings in Canada: Structural scoring system
Bibliographic record
Abstract
The National Research Council Canada recently developed a Semi-Quantitative Seismic Risk Screening Tool (SQST) for seismic risk screening of existing buildings in Canada. This paper presents the structural scoring system that is part of the SQST. The structural scoring methodology is based on FEMA P-154, but has been substantially modified to suit Canadian seismicity and seismic design and construction practices. Structural scores are obtained by adding structural basic scores and applicable score modifiers. For an existing building, a structural basic score is determined by calculating the probability of collapse on the basis of a number of assumptions. Then a series of score modifiers are calculated to address the effects of applicable building characteristics on the building’s seismic performance. The structural score is compared with an acceptable structural threshold to determine whether the structural seismic risk is acceptable. The objective of the structural scoring system is to ensure an acceptable and consistent seismic risk in building portfolios while minimizing life safety threats.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".