Determining the Actual Zinc and Iron Intakes in Breastfed Infants: Protocol for a Longitudinal Observational Study
Bibliographic record
Abstract
BACKGROUND: Zinc and iron deficiencies among breastfed infants during the first 6 months of life have been reported in previous studies. The amounts of zinc and iron intakes from breast milk are factors that contribute to the zinc and iron status of breastfed infants. OBJECTIVE: This study aims to quantitatively determine zinc and iron intakes by breastfed infants during the first 4 months of life and to investigate the factors that predict zinc and iron status in breastfed infants. METHODS: Pregnant women at 28 to 34 weeks of gestation were enrolled. Zinc and iron status during pregnancy was assessed. At delivery, cord blood was analyzed for zinc and iron levels. Participants and their babies were followed at 2 and 4 months postpartum. Maternal dietary intakes and anthropometric measurements were performed. The amount of breast milk intake was assessed using the deuterium oxide dose-to-mother technique. Breast milk samples were collected for determination of zinc and iron levels. The amount of zinc and iron consumed by infants was calculated. Zinc and iron status was determined in mothers and infants at 4 months postpartum. RESULTS: A total of 120 pregnant women were enrolled, and 80 mother-infant pairs completed the study (56 provided full breastfeeding, and 24 provided breast milk with infant formula). All data are being managed and cleaned. Statistical analysis will be done. CONCLUSIONS: This study will provide information on zinc and iron intakes in exclusively breastfed infants during the first 4 months of life and explore predictive factors and the possible association of zinc and iron intakes with infant growth and nutrient status. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/19119.
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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 | 0.023 | 0.014 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.017 | 0.005 |
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".