Comparison of high-volume air sampling equipment for viral aerosol sampling during emergency response
Bibliographic record
Abstract
OBJECTIVE: This study compared the performance of two high-volume bioaerosol air samplers for viable virus to an accepted standard low-volume sampler. In typical bioaerosol emergency response scenarios, highvolume sampling is essential for the low infective concentrations and large air volumes involved. DESIGN: Two high-volume air samplers (XMX/2LMIL and DFU-1000) were evaluated alongside a lowvolume sample (BioSampler). Low and high concentrations (9.3-93.2 agent containing particles per liter of air [ACPLA]) of male-specific coliphage 2 (MS2) virus were released into a 12 m3 aerosol test chamber and collected using the air samplers. The collection media from the samplers were then processed and viable virus was assessed via plaque assay. SETTING: Aerosol test chamber. SUBJECTS, PARTICIPANTS: None. INTERVENTIONS: Collection media and flow rate were modified for the XMX/2L-MIL sampler for viable analysis. MAIN OUTCOME MEASURES: Concentration estimates in units of plaque forming units per liter of air (PFU/liter) assessed by the samplers as compared to the levels inside the chamber as evaluated with a slit to agar plate in units of ACPLA. Comparison was made via one-way analysis of variance. RESULTS: Both the XMX/2L-MIL and DFU-1000 achieved collection effectiveness equal to or greater than the low-volume air sampler for the evaluated MS2 concentrations. The XMX/2L-MIL reliably collected quantifiable low concentrations of MS2, but the DFU-1000 was unable to do so. CONCLUSIONS: For emergency response to suspected bioaerosols, the evaluated high-volume samplers are as effective as the standard low-flow sampler and should be considered in conducting a health risk assessment. If low concentrations are expected, then high-flow samplers using liquid collection are preferred.
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".