A field comparison of four fungal aerosol sampling instruments: inter-sampler calibrations and caveats
Bibliographic record
Abstract
UNLABELLED: Four bioaerosol samplers (Reuter Centrifugal, Andersen N6 Single Stage, Surface Air System Super 90, and Air-o-Cell) were used to take c. 300 side-by-side measurements at 75 public building sites. Regression models were developed to examine the relationships between each method pair. The models demonstrate that measurements from these instruments are not directly comparable, requiring inter-instrument calibration. Sampling location (indoor vs. outdoor) was a confounder in all the pairwise comparisons between samplers. In addition, the slopes of the relationships between all method pairs except one differed in indoor vs. outdoor locations. These results emphasize that direct comparisons between methods should not be undergone without prior calibration. Where measurement circumstances are similar to those of this study, the regression models might serve as a basis to convert measurements made with one instrument to those made with another. However, the robustness and generalizability of the models in different measurement settings needs to be assessed. PRACTICAL IMPLICATIONS: Many different bioaerosol sampling devices are in common use for indoor air quality studies. If data from research studies are to be compared, an approximation of the relationships between the equipment would be useful. A comparison of three culturable sampling devices (Andersen N6, SAS 90, RCS) and one particulate sampling device (Air-o-Cell) collecting simultaneous samples under field conditions showed high linear correlations between methods. However, while direct comparisons between sampling data were not possible, the regression models reported here explained 60-85% of the variance in fungal concentrations, and underscored the importance of the effect of environment on measurement.
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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".