Assessment of pre- and postnatal exposure to polychlorinated biphenyls: lessons from the Inuit Cohort Study.
Bibliographic record
Abstract
Polychlorinated biphenyls (PCBs) are food-chain contaminants that have been shown to induce adverse developmental effects in humans. In the course of an epidemiologic study established to investigate neurodevelopmental deficits induced by environmental PCB exposure in the Inuit population of northern Québec (Nunavik, Canada), we compared three biomarkers of prenatal exposure and models to predict PCB plasma concentration at 6 months postpartum. Concentrations of 14 PCB congeners were measured by high-resolution gas chromatography with electron capture detection in lipids extracted from maternal plasma, cord plasma, breast milk (collected at approximately 1 month postpartum), and 6-month-old infant plasma samples. Similar congener profiles were observed in all biologic samples, and PCB-153, the most abundant and persistent PCB congener, was strongly correlated with other frequently detected PCB congeners in all biologic media. When expressed on a lipid basis, maternal plasma, cord plasma, and milk concentrations of this congener were strongly intercorrelated, indicating that PCB concentration in any of these biologic media is a good indicator of prenatal exposure to PCBs. A multivariate model that included maternal PCB-153 plasma lipid concentration, breast-feeding duration, and the sum of two skin-fold thicknesses (an index of infant body fat mass) explained 72% of PCB-153 plasma concentration variance at 6 months postpartum (p < 0.001). By contrast, based on the product of breast-feeding duration times the concentration of PCBs in plasma lipids, which was used as an index of postnatal PCB exposure in several studies, only 36% of infant plasma concentration was explained.
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How this classification was reachedexpand
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) | 0.000 | 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) | 0.003 | 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 teacher head, 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".