Investigation on the Lung Function of General Population in Ilam, West of Iran, as a City Exposed to Dust Storm
Bibliographic record
Abstract
BACKGROUND: Dust storm is one of the most important natural sources of air pollution in the Middle East that has caused a major concern in recent years. The aim of this study was to evaluate the respiratory tract function of people living in Ilam city (Iran) during dust storm. METHODS: A sample size of 250 people was selected and the cluster sampling was randomly used from 13 health centers in Ilam city. Pulmonary function test (PFT) was determined via a standard spirometry apparatus. Vital capacity (VC), Forced Vital capacity (FVC), FVC in first second (FEV1), FEV1/VC, FEV1/FVC, peek expiratory flow (PEF), forced expiratory flow (FEF25-75%), forced expiratory flow (FEF25-75%), forced expiratory flow (FEF75-85%), forced mid flow time (FMFT) and maximum voluntary ventilation (MVV) were measured. RESULTS: Mean values of respiratory capacities measured in all participants excluding FEV1/VC and FMFT were less than predicted mean values by ECCS reference. 21.6% of the population suffered from obstructive lesions. This value among males (24.1%) was more than females (19.6%). This could be related to more exposure (outdoor jobs) of males with dust storms. CONCLUSION: The results also showed a negative significant relationship between duration of inhabitance in Ilam city and all respiratory capacities. Further studies are needed for confident confirmation of whether reduction of respiratory capacities among Ilamian people is only related to dust storms.
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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 | 0.000 |
| 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) | 0.001 | 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".