Air pollution and daily mortality in a city with low levels of pollution.
Bibliographic record
Abstract
The concentration-response relationship between daily ambient inhalable particle (particulate matter less than or equal to 10 micro m; PM(10)) concentrations and daily mortality typically shows no evidence of a threshold concentration below which no relationship is observed. However, the power to assess a relationship at very low concentrations of PM(10) has been limited in studies to date. The concentrations of PM(10) and other air pollutants in Vancouver, British Columbia, Canada, from January 1994 through December 1996 were very low: the 50th and 90th percentiles of daily average PM(10) concentrations were 13 and 23 micro g/m(3), respectively, and 27 and 39 ppb, respectively, for 1-hr maximum ozone. Analyses of 3 years of daily pollution (PM(10), ozone, sulfur dioxide, nitrogen dioxide, and carbon monoxide) concentrations and mortality counts showed that the dominant associations were between ozone and total mortality and respiratory and cardiovascular mortality in the summer, and between nitrogen dioxide and total mortality in the winter, although some association with PM(10) may also have been present. We conclude that increases in low concentrations of air pollution are associated with increased daily mortality. These findings may support the notion that no threshold pollutant concentrations are present, but they also raise concern that these effects may not be effects of the measured pollutants themselves, but rather of some other factor(s) present in the air pollution-meteorology mix.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".