Fire Severity Outcome Comparison of Apartment Buildings Constructed from Combustible and Non-Combustible Construction Materials
Bibliographic record
Abstract
Abstract Wood is commonly used in construction, but often perceived as being less safe than structures made from non-combustible materials. With the advancement of wood products and treatment, construction techniques, and protective systems, this may not be the case any longer. Using retrospective data from fire departments across Canada, this study aimed to determine whether the type of construction material (combustible or non-combustible) affected the fire severity outcome of a one to six storey apartment building fire, after accounting for protective systems (smoke alarms and sprinklers). The study found that, after adjusting for the presence of smoke alarms and sprinklers, structures constructed from non-combustible construction materials did not perform better in terms of injuries, requiring extinguishment by fire department, or the fire spreading beyond the room of origin. The presence of working smoke alarms and sprinklers played a central role in reducing the severity outcome of a fire. Smoke alarms and sprinklers both reduced the odds of extinguishment by the fire department and the fire spreading beyond the room of origin. Sprinklers also reduced the injury rate. Overall, this study highlighted the importance of protective systems in reducing fire severity outcomes.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".