Tracking Trends in Emissions of Developmental Toxicants and Potential Associations with Congenital Heart Disease in Alberta, Canada
Bibliographic record
Abstract
Congenital heart disease (CHD) is a serious anomaly for which the etiology remains elusive. We explored temporal trend associations between industrial developmental toxicant (DT) air emissions and CHD in Alberta. Patients born between 2004–2011 with a diagnosis of CHD and 18 DTs from the National Pollutant Release Inventory (2003–2010) were identified. We applied principal component analysis (PCA) to DT amounts and toxicity risk scores (RS) and defined yearly crude CHD and septal defects rates for urban and rural regions. Correlations between DT groups and CHD rates were examined with Spearman test and Bonferroni correction was conducted for multiple comparisons. PCA identified three DT groups: Group 1 (volatile organic compounds (VOCs) and other gases,) Group 2 (other VOCs), and Group 3 (mainly heavy metals). Province-wide, we found associations between Group 1 DTs and CHD and septal defect rates, when using amounts (r = 0.86, CI 0.39, 0.97 and r = 0.89, CI 0.48, 0.98, respectively) and RS (r = 0.88, CI 0.47, 0.98 and r = 0.85, CI 0.36, 0.97, respectively). Rural Group 2 DTs were positively associated with septal defect rates in both amounts released and RS (r = 0.91, CI 0.55, 0.98 and r = 0.91, CI 0.55, 0.98, respectively). In this exploratory study, we found a temporal decrease in emissions and CHD rates in rural regions and a potential positive association between CHD and septal defect rates and mixtures of organic compounds with or without gases.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 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".