Air Health Trend Indicator: Association between Short-Term Exposure to Ground Ozone and Circulatory Hospitalizations in Canada for 17 Years, 1996–2012
Bibliographic record
Abstract
The Air Health Trend Indicator is designed to estimate the public health risk related to short-term exposure to air pollution and to detect trends in the annual health risks. Daily ozone, circulatory hospitalizations and weather data for 24 cities (about 54% of Canadians) for 17 years (1996⁻2012) were used. This study examined three circulatory causes: ischemic heart disease (IHD, 40% of cases), other heart disease (OHD, 31%) and cerebrovascular disease (CEV, 14%). A Bayesian hierarchical model using a 7-year estimator was employed to find trends in the annual national associations by season, lag of effect, sex and age group (≤65 vs. >65). Warm season 1-day lagged ozone returned higher national risk per 10 ppb: 0.4% (95% credible interval, -0.3⁻1.1%) for IHD, 0.4% (-0.2⁻1.0%) for OHD, and 0.2% (-0.8⁻1.2%) for CEV. Overall mixed trends in annual associations were observed for IHD and CEV, but a decreasing trend for OHD. While little age effect was identified, some sex-specific difference was detected, with males seemingly more vulnerable to ozone for CEV, although this finding needs further investigation. The study findings could reduce a knowledge gap by identifying trends in risk over time as well as sub-populations susceptible to ozone by age and sex.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".