Maternal and fetal exposure to cadmium, lead, manganese and mercury: The MIREC study
Bibliographic record
Abstract
Given the susceptibility of the fetus to toxicants, it is important to estimate their exposure. Approximately 2000 pregnant women were recruited in 2008-2011 from 10 cities across Canada. Cd, Pb, Mn and total Hg were measured in maternal blood from the 1st and 3rd trimesters, umbilical cord blood, and infant meconium. Nutrient intakes of vitamin D, iron, and calcium (Ca) were assessed using a food frequency questionnaire and a dietary supplement questionnaire. Median concentrations in 1st trimester maternal blood (n = 1938) were 0.20, 8.79 and 0.70 μg/L for Cd, Mn and Hg, respectively, and 0.60 μg/dL for Pb. While the median difference between the paired 1st and 3rd trimester concentrations of Cd was 0, there was a significant decrease in Pb (0.04 μg/dL) and Hg (0.12 μg/L) and an increase in Mn (3.30 μg/L) concentrations over the course of the pregnancy. While Cd was rarely detected in cord blood (19%) or meconium (3%), median Pb (0.77 μg/dL), Mn (31.87 μg/L) and Hg (0.80 μg/L) concentrations in cord blood were significantly higher than in maternal blood. Significant negative associations were observed between estimated Ca intake and maternal Cd, Pb, Mn and Hg, as well as cord blood Pb. Vitamin D intake was associated with lower maternal Cd, Pb, and Mn as well as Pb in cord blood. Even at current metal exposure levels, increasing dietary Ca and vitamin D intake during pregnancy may be associated with lower maternal blood Pb and Cd concentrations and lower Pb in cord blood.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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 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".