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 ~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
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.425 | 0.109 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".