The importance of drinking frequency in evaluating individuals' drinking patterns: implications for the development of national drinking guidelines
Bibliographic record
Abstract
AIMS: This paper examines the relationship between frequency of drinking, usual daily consumption and frequency of binge drinking, taking into consideration possible age and gender differences. PARTICIPANTS AND DESIGN: Subjects were 10 466 current drinkers (5743 women and 4723 men) aged between 18 and 76 years, who participated in the GENACIS Canada (GENder Alcohol and Culture: an International Study) study. SETTING: Canada. MEASUREMENTS: The independent variable was the annual drinking frequency. The dependent variables were the usual daily quantity consumed, annual, monthly and weekly frequency of binge drinking (five drinks or more on one occasion). FINDINGS: Logistic regressions show (i) that those who drink less than once a week are less likely than weekly drinkers to take more than two drinks when they do drink; (ii) that the usual daily quantity consumed by weekly drinkers is not related to their frequency of drinking; but that (iii) the risk and frequency of binge drinking increase with the frequency of drinking. CONCLUSIONS: Given that risk and frequency of binge drinking among Canadians increases with their frequency of drinking, any public recommendation to drink moderately should be made with great caution.
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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 | 0.031 | 0.094 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| 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 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".