Particulate matter air pollution exposure: role in the development and exacerbation of chronic obstructive pulmonary disease
Bibliographic record
Abstract
Particulate matter air pollution exposure: role in the development and exacerbation of chronic obstructive pulmonary disease Sean H Ling, Stephan F van EedenJames Hogg iCAPTURE Centre for Pulmonary and Cardiovascular Research and Heart and Lung Institute, University of British Columbia, Vancouver, British Columbia, CanadaAbstract: Due to the rapid urbanization of the world population, a better understanding of the detrimental effects of exposure to urban air pollution on chronic lung disease is necessary. Strong epidemiological evidence suggests that exposure to particulate matter (PM) air pollution causes exacerbations of pre-existing lung conditions, such as, chronic obstructive pulmonary disease (COPD) resulting in increased morbidity and mortality. However, little is known whether a chronic, low-grade exposure to ambient PM can cause the development and progression of COPD. The deposition of PM in the respiratory tract depends predominantly on the size of the particles, with larger particles deposited in the upper and larger airways and smaller particles penetrating deep into the alveolar spaces. Ineffective clearance of this PM from the airways could cause particle retention in lung tissues, resulting in a chronic, low-grade inflammatory response that may be pathogenetically important in both the exacerbation, as well as, the progression of lung disease. This review focuses on the adverse effects of exposure to ambient PM air pollution on the exacerbation, progression, and development of COPD.Keywords: chronic obstructive pulmonary disease, particulate matter, air pollution, alveolar macrophage
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".