Research on cancer: Why we need to switch the focus from mechanistic research to epidemiology and randomized trials
Bibliographic record
Abstract
A major part of medical research is based on the investigation of the biochemical and physiological processes involved in the etiology of disease. This mechanistic research is a weak tool from the perspective of helping to reduce the burden of disease. A far more fruitful strategy has been the study of lifestyle factors associated with risk of disease. Key methods in this area include epidemiology (especially cohort studies and population comparisons) and randomized controlled trials (RCTs). The focus of this paper is cancer. Recent papers estimated the proportion of cancer caused by external factors and that are therefore potentially preventable. A critical examination of these paper supports the hypothesis summarized above.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.368 | 0.584 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.011 | 0.005 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.004 | 0.034 |
| Scholarly communication | 0.018 | 0.043 |
| Open science | 0.008 | 0.008 |
| Research integrity | 0.030 | 0.048 |
| Insufficient payload (model declined to judge) | 0.012 | 0.006 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".