Toxicological Findings in Fatal Motor Vehicle Collisions in Ontario, Canada: A One‐Year Study
Bibliographic record
Abstract
Drug-impaired driving is a complex area of forensic toxicology due in part to limited data concerning the type of drugs involved and the concentrations detected. This study analyzed toxicological findings in drivers from fatal motor vehicle collisions (FMVCs) in Ontario, Canada, over a one-year period using a standardized protocol. Of the 229 cases included in the study, 56% were positive for alcohol and/or drugs. After alcohol, cannabis was the most frequently encountered substance (27%), followed by benzodiazepines (17%) and antidepressants (17%). There were differences in drugs detected by age but no marked difference in drugs detected between single and multiple FMVC's. Not all drugs detected were considered impairing either due to drug type, concentration or case history. The findings indicate the importance of comprehensive drug testing in FMVCs and highlight the need to consider a variety of factors, in addition to drug type and concentration, when assessing the role of drugs in driving impairment.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".