The association between green tea consumption and breast cancer risk: A systematic review and meta‐analysis
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
This systematic review and meta‐analysis aimed to critically evaluate the relation between green tea (GT) consumption and the risk of breast cancer. Popular electronic databases were systematically searched for papers in English language. All case‐control and cohort studies in addition to randomized clinical trials were included if they assessed the chemopreventive effects of GT on breast cancer. The quality of included studies was assessed using the Newcastle–Ottawa and Jadad scale. This systematic review comprised 14 studies: 9 case‐control studies, 4 cohort studies, and 1 clinical trial. Odds ratio (OR) in case‐control studies suggested that women in the group receiving the highest level of GT had 19% reduction in breast cancer risk compared with those who received the lowest level of GT (summary OR = 0.81, p = .031; 95% CI [0.66, 0.981]; heterogeneity, I 2 = 71.53, p < .001, random effect model; 9 studies). OR in cohort studies also showed no significant difference (OR = 0.99, p = .94; 95% CI [0.81, 1.138]; heterogeneity, I 2 = 19.06, p = .29; fixed‐effect model; 4 studies). According to the only clinical trial, treatment with GT could not alter the mammographic density compared with placebo (26% vs. 25%). It cannot be concluded that GT consumption may decrease the risk of breast cancer. Due to high heterogeneity, a pooled analysis of case‐control and cohort studies was not performed.
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 | 0.008 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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