Does a High Folate Intake Increase the Risk of Breast 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
Although not uniformly consistent, epidemiologic studies generally suggest an inverse association between dietary intake and blood measurements of folate and breast cancer risk. However, the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening trial has recently reported for the first time a potential harmful effect of high folate intake on breast cancer risk. In this study, the risk of developing breast cancer was significantly increased by 20% in women reporting supplemental folic acid intake > or = 400 microg/d compared with those reporting no supplemental intake. Furthermore, although food folate intake was not significantly related to breast cancer risk, total folate intake, mainly from folic acid supplementation, significantly increased breast cancer risk by 32%. The data from the PLCO trial support prior observations made in epidemiologic, clinical, and animal studies suggesting that folate possesses dual modulatory effects on the development and progression of cancer depending on the timing and dose of folate intervention. Based on the lack of compelling supportive evidence, routine folic acid supplementation should not be recommended as a chemopreventive measure against breast cancer at present.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 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) | 0.001 | 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