Coffee consumption and risk of type 2 diabetes, cardiovascular diseases, and cancer
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
Numerous epidemiological studies have evaluated the association between coffee consumption and risk of type 2 diabetes, coronary heart disease, and various cancers. This paper briefly reviews the evidence for a relation between coffee consumption and these conditions, with particular attention to methodological issues. Several early studies suggested that coffee consumption could result in a marked increase in risk of coronary heart disease and several types of cancer. However, more recent prospective cohort studies that are less prone to selection and information bias have not confirmed these findings. High consumption of unfiltered types of coffee, such as French press and boiled coffee, has been shown to increase low-density-lipoprotein-cholesterol concentrations. In addition, limiting caffeinated coffee intake during pregnancy seems a prudent choice. However, evidence has been accumulating that frequent consumption of coffee may reduce risk of type 2 diabetes and liver cancer. Further experimental studies are warranted to elucidate the underlying mechanisms and possibly identify the components in coffee that are responsible for these putative effects. In sum, the currently available evidence on coffee and risk of cardiovascular diseases and cancer is largely reassuring, and suggests that, for the general population, addressing other health-related behaviors has priority for the prevention of chronic diseases.
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) | 0.002 | 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