Hearts over Time: Cardiovascular Mortality Risk Linked to Long-Term PM <sub>2.5</sub> Exposure
Bibliographic record
Abstract
Adverse respiratory effects and short-term hospital admissions have been linked to acute exposure to fine particulate matter (PM 2.5 ), but few studies have examined mortality risks associated with chronic exposure.Now, in Canada's first national-level cohort study of the subject, investigators report an association between cardiovascular mortality and long-term exposure to PM 2.5 [EHP 120(5):708-714; Crouse et al.].Most research examining associations between ambient air pollution and human health has used data generated by ground-based air-pollution monitors over short periods of time.But in the current study, researchers also calculated long-term exposure levels using satellite-based estimates of ground-level PM 2.5 .Study subjects consisted of 2.1 million adults who were included in the 1991-2001 Canadian census mortality follow-up study.For residents of cities with ground-based air monitors, the investigators calculated average mean annual concentrations of PM 2.5 for the period 1987-2001 and assigned exposure levels to individuals based on their residence during that time.They also calculated exposure estimates for the whole cohort for the period 2001-2006 based on satellite remote sensing observations.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.010 | 0.007 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".