ANALYSIS OF REPEATED CROSS-SECTIONAL SURVEYS, OF PRE-SCHOOL RESPIRATORY SYMPTOMS AND TRAFFIC-RELATED AIR POLLUTION
Bibliographic record
Abstract
ISEE-135 Introduction: Traffic-related air pollution is associated with respiratory morbidity in school age children. However, there is very little information on the effects of this pollution on younger children, the age at which problems start and whether problems in early childhood persist in later life. Aim: To determine if estimates of PM10 exposure at the home address are associated with respiratory symptoms in young children and whether this association changes as the children get older. Methods: 4400 children were selected in a stratified random sample of local birth records and their parents were sent questionnaires in 1998 (children aged one to five), 2001 (aged four to eight) and again in 2003 (aged six to ten). The questionnaire asked about respiratory symptoms and relevant confounders. Logistic regression models were used to test the association between the respiratory symptoms and objective measures of exposure. The distance from home address to a major road (DHR) was used as a surrogate measure of PM10 exposure. Results: From Table 1 we can see that in all three studies cough without a cold has a significant association with DHR. Cough at night has a consistent association with DHR although this has declining significance due to falling power. Nasal symptoms are associated with DHR in all surveys. Wheeze was not significantly associated with DHR in any year. After adjusting for relevant confounders the results were largely unchanged.Table 1: Association between distance to a major road (per 100m) and chronic respiratory symptoms during the past 12 monthsDiscussion: Both cough and nasal symptoms have a significant association with an objective exposure to traffic related air pollution in pre-school children. This association persists through early childhood. This association is less clear for wheeze.
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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 | 0.010 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".