Impact of global short-term landscape fire sourced PM2.5 exposure on child cause-specific morbidity: a study in multiple countries and territories
Bibliographic record
Abstract
Abstract Children are particularly vulnerable to landscape fire sourced fine particulate matter (LFS PM 2.5 ), yet evidence on its health effects remains limited. Here we show that short-term exposure to LFS PM 2.5 is associated with increased hospital admissions for multiple diseases in children and adolescents. We analysed daily hospital admission data from 1012 communities in seven countries/territories, linked to a high-resolution LFS PM 2.5 dataset. Each 10 μg/m 3 increase in LFS PM 2.5 was associated with elevated risks for all-cause (1.1%), respiratory (1.9%), infectious (1.5%), cardiovascular (2.9%), neurological (2.8%), diabetes (3.7%), cancer (1.5%), and digestive (0.8%) hospital admissions. Risks for respiratory, infectious, and neurological conditions increased even at low exposure, while others rose only above 15-20 μg/m 3 . Children aged 5-9 years and those in lower socioeconomic areas were especially affected. These findings highlight the health burden of LFS PM 2.5 in young people and the urgent need to reduce exposure and protect vulnerable populations.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".