Cancer incidence and mortality attributable to alcohol consumption
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 is a major cause of disease and death. In a previous study, we reported that in 2002, 3.6% of all cases of cancer and a similar proportion of cancer deaths were attributable to the consumption of alcohol. We aimed to update these figures to 2012 using global estimates of cancer cases and cancer deaths, data on the prevalence of drinkers from the World Health Organization (WHO) global survey on alcohol and health, and relative risks for alcohol-related neoplasms from a recent meta-analysis. Over the 10-year period considered, the total number of alcohol-attributable cancer cases increased to approximately 770,000 worldwide (5.5% of the total number of cancer cases)-540,000 men (7.2%) and 230,000 women (3.5%). Corresponding figures for cancer deaths attributable to alcohol consumption increased to approximately 480,000 (5.8% of the total number of cancer deaths) in both sexes combined-360,000 (7.8%) men and 120,000 (3.3%) women. These proportions were particularly high in the WHO Western Pacific region, the WHO European region and the WHO South-East Asia region. A high burden of cancer mortality and morbidity is attributable to alcohol, and public health measures should be adopted in order to limit excessive alcohol consumption.
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 | 0.000 | 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 it