Perfluorinated alkyl substances in Canadian human milk as part of the Maternal-Infant Research on Environmental Chemicals (MIREC) study
Bibliographic record
Abstract
Perfluorinated alkyl substances (PFAS) were determined in human milk samples (n = 664) from participants in the Maternal-Infant Research on Environmental Chemicals (MIREC) study. ΣPFAS concentrations (sum of seven PFAS) ranged from 3.1 ng L−1 to 603 ng L−1, with a median concentration of 106 ng L−1 in the Canadian mothers' milk analyzed. These data comprise the first pan-Canadian dataset of PFAS in human milk. Perfluorooctanoic acid (PFOA) and linear perfluorooctanesulfonate (L-PFOS) were the dominant contributors to ΣPFAS in human milk samples. An inverse relationship between ΣPFAS concentrations and age was observed (Spearman correlation - 0.184). Primiparous women had elevated PFAS concentrations in milk relative to women who had children previously (p < 0.001). In contrast, the region of maternal birth did not influence ΣPFAS concentrations (p = 0.156). Although China and Norway have observed consistently detectable levels of perfluoroundecanoic acid (PFUdA) in human milk, PFAS with long carbon chains (n ≥ 11) were not present above method detection limits in Canadian human milk samples analyzed as part of the MIREC study. In conclusion, despite the presence of low levels of environmental contaminants in human milk, Health Canada supports breastfeeding due to the benefits to both infants and mothers.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".