Capturing the Aerobiome: Application of Polyurethane Foam Disk Passive Samplers for Bioaerosol Monitoring
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Bioaerosols are ubiquitous and play a significant role in global climate and human health due to inhalation exposure. Passive air sampling of bioaerosols, as a complementary method to active sampling using pumps, is increasingly valued due to its simplicity, electricity-free operations, and cost-effectiveness in providing time-integrated samples over weeks/months. In this study, polyurethane foam disk passive air samplers (PUF-PAS), passive dry deposition air samplers (PAS-DDs), and active high-volume (Hi-Vol) air samplers were deployed in Toronto and the Athabasca oil sands region (OSR) in the first stages of a proof-of-concept exercise for bioaerosols. Airborne bacterial and fungal communities were characterized using MiSeq DNA sequencing. All sampler types were shown to successfully collect bioaerosols. The dominant bacterial and fungal phyla observed by all samplers were qualitatively similar. Species richness and community structure of the airborne bacterial and fungal communities varied with sites and seasons. Principal coordination analysis indicated that bacterial and fungal communities differed between Toronto and OSR. Further work is required to calibrate and characterize the uptake of PUF-PAS and PAS-DD for bioaerosols to derive quantitative information on their abundance to better assess sources and potential exposure risks.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".