The relative risks and etiologic fractions of different causes of death and disease attributable to alcohol, tobacco and illicit drug use in Canada.
Bibliographic record
Abstract
BACKGROUND: In 1996 the number of deaths and admissions to hospital in Canada that could be attributed to the use of alcohol, tobacco and illicit drugs were estimated from 1992 data. In this paper we update these estimates to the year 1995. METHODS: On the basis of pooled estimates of relative risk, etiologic fractions were calculated by age, sex and province for 90 causes of disease or death attributable to alcohol, tobacco or illicit drugs; the etiologic fractions were then applied to national mortality and morbidity data for 1995 to estimate the number of deaths and admissions to hospital attributable to substance abuse. RESULTS: In 1995, 6507 deaths and 82,014 admissions to hospital were attributed to alcohol, 34,728 deaths and 194,072 admissions to hospital were attributed to tobacco, and 805 deaths and 6940 admissions to hospital were due to illicit drugs. INTERPRETATION: The use and misuse of alcohol, tobacco and illicit drugs accounted for 20.0% of deaths, 22.2% of years of potential life lost and 9.4% of admissions to hospital in Canada in 1995.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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".