Semi-quantitative seismic risk screening tool for existing buildings in Canada
Bibliographic record
Abstract
The National Research Council of Canada (NRC) recently developed a semi-quantitative seismic risk screening tool (SQST) for existing buildings in Canada. The SQST is intended to supersede the Manual for Screening of Buildings for Seismic Investigation developed by the NRC in the early 1990s. The SQST consists of three key components: (i) a structural scoring system that quantitatively assesses the structural seismic risk based on probability of collapse; (ii) a nonstructural component scoring system that qualitatively assesses the seismic risk of nonstructural components based on seismic demand; and (iii) a ranking procedure that prioritizes potentially hazardous buildings for seismic evaluations and possible upgrading. The intent of the SQST is to inexpensively identify and exempt buildings with acceptable life safety risk and optimize the allocation of resources to assess the seismic risks to portfolios of buildings. Seismic screening with the SQST can be completed with either paper-based screening forms or a web-based application. The applicability of the SQST was demonstrated with a pilot study for 33 existing buildings across Canada.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.001 |
| Bibliometrics | 0.007 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.013 | 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".