Trend of alcohol use disorder as a percentage of all-cause mortality in North America
Bibliographic record
Abstract
OBJECTIVE: To evaluate the trend of alcohol use disorder (AUD) mortality as a percentage of all-cause mortality in Canada and the United States (US) between 2000 and 2019, by age group. RESULTS: Joinpoint regression showed that AUD mortality as a percentage of all-cause mortality significantly increased between 2000 and 2019 in both countries, and across all age groups (i.e., young adults (20-34 years), middle-aged adults (35-49 years), and older adults (50 + years)). The trend has been levelling off, and even reversing in some cases, in recent years. The average annual percentage change differed across countries and between age groups, with a greater increase among Canadian adults aged 35-49 years and among adults aged 50 + years in the US. Over the past two decades, AUD mortality as a percentage of all-cause mortality has been increasing among all adults in both Canada and the US.
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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 | 0.001 | 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 | 0.000 | 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".