Alcohol and drug consumption by quebec truck drivers
Bibliographic record
Abstract
The Société de l’assurance automobile du Québec conducted a roadside survey in June 2001 on truck drivers to assess their use of alcohol and/or drugs. SAAQ motor carrier enforcement officers intercepted a total of 2,803 truckers who were asked to take part in the survey, of whom 2,679 (96%) eligible drivers agreed to participate. Of that number, 2,172 (81%) gave a urine sample, 2,541(95%) a saliva sample and 2,629 (98%) a breath sample. Chemists at the Centre de toxicologie du Québec were entrusted with analysis of the biological samples. The roadside collection of samples required elaborate planning. Achieving optimal participation was kept in mind in setting up the survey, which was considered in that light under all its aspects. Only two truck drivers (0.03 %) had a BAC above 0.08, while another 6 (0.2 %) had a BAC between 0.02 and 0.08. According to the toxicological analysis of urine samples, drugs were found in the following proportions: cannabis (4,8 %) , amphetamines (2,9%), cocaine (1,4 %), opiates (0,6%) and benzodiazepines (0,3%)
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 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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".