Wheezy Episodes as a Function of Time-Variant Exposure to Point Source of Air Pollution
Bibliographic record
Abstract
ISEE-819 Objective: To assess risk of acute episodes of wheezy respiratory disease among children living around industrial refinery stacks as a function of hours of from-refinery wind exposure, and (separately) of daily exposure to stack-generated SO2. Materials and Methods: In previous work, we found that the 20,000 <15-year-old children who live within 3 km of a Montreal petroindustrial zone experience twice the annual background rate of hospitalizations for asthma, bronchiolitis, and other wheezy respiratory diseases. Based on electronic claims records of medical visits and hospitalizations from Quebec's universal health services system, we developed a 12-year file of health care contacts by day for the diagnoses of interest. Children's addresses, at the level of a city street block, were attached. Exposure assessment was based on (a) hours of wind blowing from the industrial site toward children's homes; (b) the difference in monitored SO2 at fixed sites down- minus up-wind of children's residences with respect to the zone; and (c) a plume model of daily residence-specific SO2 concentrations. We considered lagged exposure-to-disease scenarios of up to 5 days. Medical data were coupled to environmental measures through case-only designs, where SO2 concentration gradients related to the odds of cases occurring in the impacted versus distant sectors, and case-crossover designs where odds of acute case presentation were expressed by hours of off-sector winds, and separately as a function of residence-specific SO2 estimates in the hazard versus control periods. Results: Initial results indicate moderate impacts of time-variant exposure to both winds and to increasing SO2 levels on the odds of presentation for acute wheezy disease. Final results will be available by September. Conclusions: New epidemiologic methods allow for the assessment of time-variant exposure to point sources of pollution on the risk of acute episodes of respiratory disease.
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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 | 0.006 | 0.002 |
| 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) | 0.001 | 0.001 |
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".