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Record W4415507621 · doi:10.1093/clinchem/hvaf126

Challenges in Responding to Cannabis-Impaired Motor Vehicle Drivers

2025· article· en· W4415507621 on OpenAlexaboutno aff
Wayne Hall, Johannes G. Ramaekers

Bibliographic record

VenueClinical Chemistry · 2025
Typearticle
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsnot available
Fundersnot available
KeywordsHuman factors and ergonomicsPoison controlInjury preventionMotor vehicle crashOccupational safety and healthVehicle safety

Abstract

fetched live from OpenAlex

Cannabis is a drug that is widely used in North America, Europe, and Oceania (1) by young adults ages 18 to 25 years who are at the highest risk of being in motor vehicle crashes that injure or kill them and other drivers (2). Its use has been shown in laboratory and road studies (3) to impair driving performance, and governments have introduced policies to discourage cannabis use by drivers (4, 5). A study by Fitzgerald et al. (6) in the current issue raises serious doubts about the scientific validity of using measures of Δ9-tetrahydrocannabinol (THC; the primary active ingredient of cannabis) in blood to identify cannabis-impaired drivers. Jurisdictions in Australia, Canada, Europe, and the United States have passed laws that specify various levels of THC in blood (e.g., 2 ng/mL or 5 ng/mL) as prima facie evidence that a driver was impaired by cannabis (5). Some jurisdictions have passed zero-tolerance laws that treat any detectable level of THC in blood (e.g., >0.5 ng/mL) as evidence of cannabis-impaired driving (5).

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.118
Threshold uncertainty score0.554

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.074
GPT teacher head0.409
Teacher spread0.335 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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