Limited data exist to inform our basic understanding of micronutrient requirements in pregnancy
Bibliographic record
Abstract
Women and pregnant people have historically been underrepresented in research; this may extend to the basic research informing nutrient reference values, such as the United States’ and Canada’s Dietary Reference Intakes (DRIs). After screening the DRI reports for 23 micronutrients, we extracted metadata from 704 studies. Women were excluded in 23% of studies, and they accounted for a smaller proportion of the sample size (29%). Pregnant or lactating people were included in 17% of the studies. Studies that used rigorous design elements, such as controlled feeding and stable isotope studies, were the most likely to include men only. The majority of studies (>90%) did not report race and ethnicity. Although nutrient reference values are intended for use in the general population, we find that the basic science informing these values may not be generalizable. We call urgently upon funders and researchers to address fundamental gaps in knowledge with high-quality research.
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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 | 0.081 | 0.401 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.012 | 0.014 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.006 | 0.010 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.023 | 0.003 |
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".