Recommendations for toxicological investigation of drug-impaired driving and motor vehicle fatalities—2025 update
Bibliographic record
Abstract
This article describes updates to previously published recommendations for drug testing in drug-impaired driving cases. A survey of drug testing practices in driving under the influence of drug and motor vehicle fatality cases was sent to toxicology laboratories across the USA and Canada. Following the compilation of survey data, a virtual consensus meeting was held where forensic science practitioners and the authors reviewed the survey results and conducted a comprehensive review of the 2021 recommendations using a modified Delphi method. Tier I and Tier II screening and confirmation scope and cutoffs were re-evaluated to update the recommendations. Carisoprodol and meprobamate were moved to the Tier II scope from Tier I; gabapentin was promoted to the Tier I scope from Tier II; screening cutoffs were differentiated for immunoassay versus non-immunoassay (e.g. chromatographic) screening for blood and oral fluid; cross-reactivity screening requirements were removed and clarified with specific cutoff values; several cutoffs for screening and confirmation were increased or removed for blood and oral fluid; urine was removed as a recommended matrix for testing in cases involving suspected drug impairment.
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 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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 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".