A field comparison of four samplers for enumerating fungal aerosols I. Sampling characteristics
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
UNLABELLED: This study compared the performance of four bioaerosol samplers, the Reuter Centrifugal Air Sampler, the Andersen N6 single stage, the Surface Air System 90, and the Air-o-Cell, in measurements for airborne fungal propagules collected in 75 public building sites without prior knowledge of water damage or mold problems in British Columbia, Canada. The samplers had differences in detection limits, reproducibility, and overall yield. However, high and significant correlations between samplers (indoor samples: Pearson r = 0.60-0.85, P < 0.001) suggest that relative performances between samplers were reasonably consistent. These results indicate that fungal airborne concentration data are dependent on the methods used for assessment, and introduce additional variability in exposure assessment studies. PRACTICAL IMPLICATIONS: In the absence of a standard protocol for sampling bioaerosols, the interpretation of aerosol data reported in indoor air quality studies is entirely dependent on an appreciation of the sampling characteristics of commonly used instrumentation. Although a number of comparative studies have been undertaken in the laboratory, only a few studies have made reported comparison data under field conditions. This study compared three culturable sampling devices, the Andersen N6, SAS 90, and RCS, and one particulate sampling device, the Air-o-Cell, in offices and public areas in a variety of buildings, under conditions of forced air or natural ventilation. The concentrations of fungal aerosols collected during simultaneous sample collection were highly correlated, yet varied by orders of magnitude. The performance of these devices must be carefully considered before a standard protocol can be promulgated.
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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 it