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
AIMS: To estimate avoidable burden and avoidable costs of alcohol abuse in Canada for the year 2002. METHODS: A policy effectiveness approach was used. The impact of six effective and cost-effective alcohol policy interventions aimed to reduce alcohol consumption was modeled. In addition, the effect of privatized alcohol sales that would increase alcohol consumption and alcohol-attributable costs was also modeled. The effects of these interventions were compared with the baseline (aggregate) costs obtained from the second Canadian Study of Social Costs Attributable to Substance Abuse. RESULTS: It was estimated that by implementing six cost-effective policies from about 900 million to two billion Canadian dollars per year could be saved in Canada. The greatest savings due to the implementation of these interventions would be achieved in the lowering of productivity losses, followed by health care, and criminality. Substantial increases in burden and cost would occur if Canadian provinces were to privatize alcohol sales. CONCLUSION: The implementation of proven effective population-based interventions would reduce alcohol-attributable burden and its costs in Canada to a considerable degree.
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) | 0.000 | 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 | 0.001 |
| 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 it