A review of particulate matter emissions and impacts on human health: A focus on Canadian agricultural and rural emission sources
Bibliographic record
Abstract
Particulate matter (PM) has been documented in an increasing number of research studies as having a known or suspected negative impact on human health. The World Health Organization (WHO) estimates that 3.1 million deaths were caused by ambient fine particulate matter (PM2.5) in 2010. While many Canadian studies focus on health impacts from PM2.5, there is a gap with respect to rural sourced PM2.5 and health impacts in these areas. This paper reviews the impact PM2.5 has on Canadians’ health, investigates where PM2.5 data is being gathered, and outlines the sources of PM2.5 reported. Secondary inorganic aerosols that are formed in and around animal production facilities due to the higher prevalence of ammonia gas is of particular interest. The conclusion drawn is that the reporting and gathering of rural sourced PM2.5 data is lacking, leading to a gap in the data used to determine the impacts on Canadian human health.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.008 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".