Bibliographic record
Abstract
Burnt remains and fire-related research are growing areas of investigation in forensic anthropology; however, for this research to be valuable to criminal death investigations it must be comparable with real death circumstances. To ensure this relevance, an understanding of the circumstances (and victim profiles) relating to fatal fires is required. As a first step in addressing these issues, this paper examines and interprets fire deaths occurring in Alberta, Canada over a ten-year period between January 1999 and December 2008. The results show that 274 individuals died in 231 fire incidents during the period under review. The majority of these deaths occurred in residential fires (65%), vehicle fires following vehicle collisions (20%) and stationary vehicle fires (8%). Analysis also indicates that the victim and burn profile vary with fire type. In residential fires, young and elderly individuals are at risk whereas in vehicle fires following vehicle collisions, middle-aged adults are the most common victims. Victims of residential fires exhibit varying degrees of burn damage and remains may be reduced to calcined bone fragments. More severe burning is seen in trailer or cabin fires compared to house fires. In vehicle fires, burn damage is often significant, with remains frequently exhibiting thermal amputation. Fatal residential and stationary vehicle fires are more common in the winter and spring seasons, in contrast to vehicle fires following vehicle collisions which occur most often in the fall.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.011 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".