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Record W755689308

DRUG USE AMONG QUEBEC DRIVERS: THE 1999 ROADSIDE SURVEY

2000· article· en· W755689308 on OpenAlexaboutno aff
Christian Dussault, A M Lemire, Jonathan Bouchard, M Brault

Bibliographic record

VenueProceedings International Council on Alcohol, Drugs and Traffic Safety Conference · 2000
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicForensic Toxicology and Drug Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental healthCannabisGeographyMedicineDemographyPsychiatry
DOInot available

Abstract

fetched live from OpenAlex

As part of a major undertaking to establish the role of drugs in highway collisions, the Societe de l'assurance automobile du Quebec (SAAQ) conducted a roadside survey from August 9 to August 29, 1999 in order to determine drug use among Quebec drivers. Regardless of time of day, a BAC above the legal limit (.08) was found in 0.8% of the breath samples. When using the same time period (9 PM to 3 AM, Wednesday to Sunday) as in previous alcohol roadside surveys, BAC>.08 was found in 1.8% (+/- 0.5%) of breath samples in 1999 (n = 2724) which compares to 3.2% in 1991, 3.6% in 1986 and 5.9% in 1981. According to the toxicological analysis of the 2281 urine samples, drugs were found in the following proportions: cannabis (5.22%), benzodiazepines (3.66%), cocaine (1.09%), opiates (1.08%), barbiturates (0.35%), amphetamines (0.07%), PCP (0.03%). However, large variations are observed depending on the time of day, sex and age. For the covering abstract see ITRD E106992.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.131
GPT teacher head0.346
Teacher spread0.215 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations19
Published2000
Admission routes1
Has abstractyes

Explore more

Same venueProceedings International Council on Alcohol, Drugs and Traffic Safety ConferenceSame topicForensic Toxicology and Drug AnalysisFrench-language works237,207