The effects of air pollution on the health of children
Bibliographic record
Abstract
The present article is intended to inform paediatricians about the associations between ambient air pollution and adverse health outcomes in children within the context of current epidemiological evidence.The majority of the current literature pertains to adverse respiratory health outcomes, including asthma, other respiratory symptoms, and deficits in lung function and growth, as well as exposure to ambient levels of criteria air pollutants. In addition to the above, the present article highlights mortality, pregnancy outcomes, vitamin D deficiency and alteration in the immune system of children.Some of the data on the impact of improved air quality on children's health are provided, including the reduction of air pollution in former East Germany following the reunification of Germany, as well as the reduction in the rates of childhood asthma events during the 1996 Summer Olympics in Atlanta, Georgia, due to a reduction in local motor vehicle traffic. However, there are many other toxic air pollutants that are regularly released into the air. These pollutants, which are not regularly monitored and have not been adequately researched, are also potentially harmful to children.Significant morbidity and mortality is attributed to ambient air pollution, resulting in a significant economic cost to society. As Canada's cities grow, air pollution issues need to be a priority in order to protect the health of children and support sustainable development for future generations.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".