Residential fire scenario analysis in Ontario 1995-2003
Bibliographic record
Abstract
This report identifies some very important features of fatal fires in Ontario. It locates, for example, the victims' position in the houses and tentatively explains why the victims were unable to save themselves. It provides sufficient details to indicate research that can be undertaken to help make homes a safer place to live. Based on the Ontario data for the period 1995-2003, residential fires occurred most frequently in the kitchen and cooking areas. However, fatal fires are more frequent in living rooms (45.1% of fatalities) and are in general caused by a smoker's materials such as cigarettes, cigars, matches, lighters, etc. used in conjunction with smoking (37.4% of fire deaths). When a deadly fire breaks out, most of the time, upholstered furniture is the first material to be ignited (26% of fire deaths). The most probable levels for fatal fires to occur in Ontario houses are on the ground floor (59 % of deaths), the second stories (17.3% of deaths), the basements (14.8% of deaths), and the third floors (3.9 % of deaths). Fire kills because, in part, the victims are either too young or too old to react quickly and effectively to a fire emergency.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".