Influence of observational study design on the interpretation of cancer risk reduction by carotenoids
Bibliographic record
Abstract
Recently published literature has been reviewed to determine whether lycopene, beta-carotene, alpha-carotene, and beta-cryptoxanthin are associated with reductions in cancer risk and whether study findings differ by study design. A total of 57 publications meeting pre-defined inclusion and exclusion criteria were identified, with the majority (55) being observational studies. None of the intervention studies supported a significant reduction in cancer risk with carotenoid (beta-carotene) supplementation. The majority of observational studies did not support significant reductions in cancer risk with increased carotenoid dietary intakes/circulating levels. A larger percentage of case-control studies supported significant associations between increased dietary intakes/circulating levels of carotenoids relative to prospective (cohort and nested case-control) studies. Compared to prospective studies, case-control studies cannot be used to establish temporality and may be more susceptible to selection and recall biases. Thus, diet-disease relationships suggested by case-control studies should ideally be confirmed by additional evidence from prospective studies.
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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 | 0.118 | 0.314 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.004 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".