A two-year review of cocaine findings in impaired driving investigations in Ontario, Canada
Bibliographic record
Abstract
Drug-impaired driving is an increasing public safety concern across Canada, particularly due to the demonstrated increase in use of recreational drugs such as cocaine. Cocaine is a central nervous system stimulant drug; however, it can impair an individual's driving ability in both the stimulant and crash phases. Despite the scientific consensus regarding cocaine's potential for driving impairment, there is relatively little information available regarding blood concentrations and associated observations of impairment in suspected impaired drivers. Retrospective data analysis was performed to evaluate suspected impaired driving cases in which cocaine and/or benzoylecgonine were detected alone, or in combination with other drugs, in blood and urine samples submitted to the Toxicology Section of the Centre of Forensic Sciences with incident dates between 2021 and 2022. Cocaine and/or benzoylecgonine were detected in 46% (blood) and 66% (urine) of the total impaired driving samples submitted. In 41 cases where cocaine and/or benzoylecgonine were the only drug finding in blood, concentrations of cocaine and benzoylecgonine ranged from 0.0073 to 0.26 mg/L (mean 0.096 mg/L) and 0.13 to 5.3 mg/L (mean 2.1 mg/L), respectively. Driving observations reported by the arresting officer in cases where cocaine and/or benzoylecgonine were the only drug finding in blood and urine included the driver being involved in a collision, the vehicle leaving the roadway, erratic driving and the driver being asleep at the wheel; observations of drug impairment reported by the drug recognition expert at the time of driver evaluation included abnormal speech patterns, poor balance/incoordination, abnormal body movements and the individual falling asleep. The results provide concentrations of cocaine and benzoylecgonine observed in suspected impaired drivers, insight into observations that may be associated with prior cocaine use and additional information to inform on the effects of cocaine on driving.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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 teacher head, 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".