Acute Effects of Cannabis on Young Drivers' Performance of Driving Related Skills
Bibliographic record
Abstract
Impaired driving is a major source of preventable death in Canada, especially among young adults. Although the effects of alcohol on driving are well known, the impact of driving under the influence of cannabis has not been studied as thoroughly. This human laboratory study examines the impact of an acute dose of smoked cannabis on driving-related skills among young drivers who use cannabis regularly. Participants were weekly smokers between the ages of 19 and 25 years who have had an Ontario class G or G2 license for at least twelve months. Measures of driving simulator performance, cognition, mood, and motor skills were collected before and after a single dose of smoked cannabis containing 12.5% á 9- tetrahydrocannabinol (á 9-THC). Although the data presented are based on an interim analysis of an ongoing study, some measures of subjective drug effects, objective physical measures, and driving simulator performance were found to be significantly altered after drug administration.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".