Persistent organic pollutants (POPs) and metals in primiparous women: a comparison from Canada and Mexico
Bibliographic record
Abstract
Under the North American Commission for Environmental Cooperation (CEC) and its Sound Management of Chemicals (SMOC) program, a tri-national human contaminant monitoring initiative was completed to provide baseline exposure information for several environmental contaminants in Canada, Mexico and the United States (U.S). Blood samples were collected from primiparous women in Canada and Mexico, and were analysed for a suite of environmental contaminants including polychlorinated biphenyls (PCBs), dichlorodiphenyldichloroethylene(p,p'-DDE),beta-hexachlorocyclohexane (β-HCH), mercury and lead. A multiple stepwise linear regression analysis was conducted using data from Canadian and Mexican primiparous mothers, adjusting for ethnicity group, age, pre-pregnancy BMI, years at current city and ever-smoking status. Concentrations of p,p'-DDE, β-HCH, and lead were found to be higher among Mexican participants; however, concentrations of most PCBs among Mexican participants were similar to Canadian primiparous women after adjusting for covariates. Concentrations of total mercury were generally higher among Mexican primiparous women although this difference was smaller as age increased. This initial dataset can be used to determine priorities for future activities and to track progress in the management of the selected chemicals, both domestically and on a broader cooperative basis within North America.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 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) | 0.003 | 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 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".