Generation and Homogeneity of Aerosols in a Human Whole-Body Inhalation Chamber
Bibliographic record
Abstract
INTRODUCTION: A 16 m(3) whole-body exposure chamber for human exposure to aerosols is described. Several modifications of the aerosol generation and distribution system were needed to ensure a stable aerosol concentration in the chamber, especially when a cyclone pre-classifier was used. RESULTS: After these modifications, stable aerosol concentrations of aluminium oxide with a volume median diameter of 5.7 microm, and approximately 3 microm when the cyclone was used, could be achieved after 1 h of aerosol generation. Aerosol concentrations of 1-8 mg m(-3) generated without the cyclone could be maintained for at least 2 h after the aerosol level had stabilized. The temporal variability [coefficient of variation (CV)] of the aerosol concentration was 4-6%, while concentrations <1 mg m(-3) showed greater relative variability. The spatial variability at 3.8 mg m(-3) without a volunteer in the chamber was 4.8%. With a volunteer in the chamber who performed 30 min of ergometric cycling during 2 h of aerosol exposure, the exposure estimated by personal sampling was 15-17% lower than monitored with an optical particle counter. The variability of personally measured exposure was higher than of stationary measurements showing CVs of 10-19%. CONCLUSIONS: These results show that controlled exposure of human volunteers to a range of concentrations can be achieved with good accuracy in this inhalation chamber. The results compare favourably with other chambers described in the literature. Personal sampling showed lower aerosol concentrations than estimated in an empty chamber and the variability was significantly higher than measured stationary.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".