A time-series analysis of acidic particulate matter and daily mortality and morbidity in the Buffalo, New York, region.
Bibliographic record
Abstract
A component of particulate matter (PM) air pollution that may provide one biologically plausible pathway for the observed PM air pollution-health effect associations is aerosol acidity (H(+)). An increasing number of observational studies have demonstrated associations between H(+) and increased adverse health effects in the United States and abroad. Although studies have shown significant H(+) associations with increased morbidity in the United States, similar associations have yet to be shown with daily mortality. We considered a 2.5-year record of daily H(+) and sulfate measurements (May 1988-October 1990) collected in the Buffalo, New York, region in a time-series analysis of respiratory, circulatory, and total daily mortality and hospital admissions. Other copollutants considered included particulate matter [less than/equal to] 10 microm in aerodynamic diameter, coefficient of haze, ozone, carbon monoxide, sulfur dioxide, and nitrogen dioxide. Various modeling techniques were applied to control for confounding of effect estimates due to seasonality, weather, and day-of-week effects. We found multiple significant pollutant-health effect associations--most strongly between SO(4)(2-) and respiratory hospital admissions (as indicated by its t-statistic). Additionally, H(+) and SO(4)(2-) demonstrated the most coherent associations with both respiratory hospital admissions [H(+): relative risk (RR) = 1. 31; 95% confidence interval (CI), 1.14-1.51; and SO(4)(2-): RR = 1. 18, CI, 1.09-1.28] and respiratory mortality (H(+): RR = 1.55, CI, 1. 09-2.20; and SO(4)(2-): RR = 1.24, CI, 1.01-1.52). Thus, acidic sulfate aerosols represent a component of PM air pollution that may contribute to the previously noted adverse effects of PM mass on human health, and the associations demonstrated in this study support the need for further investigations into the potential health effects of acidic aerosols.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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 teacher head, 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".