Reduction of Drinking in Problem Drinkers and All-Cause Mortality
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Alcohol consumption has been linked with considerable mortality, and reduction of drinking, especially of heavy drinking, has been suggested as one of the main measures to reduce alcohol-attributable mortality. Aggregate-level studies including but not limited to natural experiments support this suggestion; however, causality cannot be established in ecological analysis. The results of individual-level cohort studies are ambiguous. On the other hand, randomized clinical trials with problem drinkers show that brief interventions leading to a reduction of average drinking also led to a reduction of all-cause mortality within 1 year. The results of these studies were pooled and a model for reduction of drinking in heavy drinkers and its consequences for all-cause mortality risk was estimated. Ceteris paribus, the higher the level of drinking, the stronger the effects of a given reduction. Implications for interventions and public health are discussed.
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.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 it