Industrial Developmental Toxicants and Congenital Heart Disease in Urban and Rural Alberta, Canada
Bibliographic record
Abstract
The etiology of congenital heart defects (CHD) is not known for many affected patients. In the present study, we examined the association between industrial emissions and CHD in urban and rural Alberta. We acquired the emissions data reported in the Canadian National Pollutant Release Inventory (n = 18) and identified CHD patients born in Alberta from 2003–2010 (n = 2413). We identified three groups of emissions after principal component analysis: Groups 1, 2, and 3. The distribution of exposure to the postal codes with births was determined using an inverse distance weighted approach. Poisson or negative binomial regression models helped estimate associations (relative risk (RR), 95% Confidence Intervals (CI)) adjusted for socioeconomic status and two criteria pollutants: nitrogen dioxide and particulate matter with a mean aerodynamic diameter of ≤2.5 micrometers. The adjusted RR in urban settings was 1.8 (95% CI: 1.5, 2.3) for Group 1 and 1.4 (95% CI: 1.3, 1.6) for both Groups 2 and 3. In rural postal codes, Groups 1 and 3 emissions had a RR of 2.6 (95% CI: 1.03, 7). Associations were only observed in postal codes with the highest levels of emissions and maps demonstrated that regions with very high exposures were sparse.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".