Synoptic weather patterns and modification of the association between air pollution and human mortality
Bibliographic record
Abstract
To assess whether meteorological conditions modify the relationship between short-term exposure to ambient air pollution and mortality, an examination of air pollution and human mortality associations (ecologic) using hybrid spatial synoptic classification procedures was conducted. Concentrations of air pollutants and human mortality from all non-accidental and cardiorespiratory causes were examined according to typical winter and summer synoptic climatologies in Toronto, Canada, between 1981 and 1999. Air masses were derived using a hybrid spatial synoptic classification procedure associating each day over the 19-year period with one of six different typical weather types, or a transition between two weather types. Generalized linear models (GLMs) were used to assess the risk of mortality from air pollution within specific air mass type subsets. Mortality follows a distinct seasonal pattern with a maximum in winter and a minimum in summer. Average air pollution concentrations were similar in both seasons with the exception of elevated sulfur dioxide levels in winter and elevated ozone levels in summer. Subtle changes in meteorological composition can alter the strength of pollutant associations with health outcomes, especially in the summer season. Although there does not appear to be any systematic patterning of modification, variation in pollutant concentrations seems dependent on the type of synoptic category present.
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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 | 0.002 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".