Folic acid fortified milk increases blood folate to concentrations associated with a very low risk of neural tube defects in Singaporean women of childbearing age.
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Folic acid (400 μg/d) taken during the periconceptional period reduces neural tube defect (NTD) risk by >75%. Achieving red cell folate (RCF) or plasma folate (PF) >905 nmol/L and >35 nmol/L, respectively, has been associated with a low risk of NTDs. We determined whether daily consumption of folic acid fortified milk increases blood folate concentrations to levels associated with a low risk of NTDs in Singaporean women of childbearing age. METHODS AND STUDY DESIGN: In this double-blind placebo-controlled trial, 70 non-pregnant women (21-35 y) were randomly assigned to receive fortified milk (FM) powder providing 400 μg folic acid per day or unfortified placebo milk (PM) powder for 12 weeks. Blood samples were collected at baseline and at 6 and 12 weeks. RESULTS: At 12 weeks, mean (95% CI) RCF and PF concentrations were 376 (240, 512) and 39 (26, 51) nmol/L higher in the FM group compared with the PM group (p<0.001). Of the women receiving FM, 71% (n=25) and 86% (n=30) achieved a RCF and PF associated with a very low risk of NTDs, respectively. CONCLUSION: Folic acid fortified milk increased blood folate concentrations in women of childbearing age to levels associated with a reduced risk of an NTD-affected pregnancy.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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 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".