Field detection and identification of a bioaerosol suite by pyrolysis‐gas chromatography‐ion mobility spectrometry*
Bibliographic record
Abstract
Abstract Improvements were made to a pyrolysis‐gas chromatography‐ion mobility spectrometry (Py‐GC‐IMS) stand‐alone biodetector to provide more pyrolyzate compound information to the IMS detector module. Air carrier gas flowing continuously through the pyrolysis tube, the rate of air flow, and pyrolysis rate were found to improve the relative quality and quantity of pyrolyzate compounds detected by the IMS detector compared to earlier work. These improvements allowed a greater degree of confidence in the correlation of biological aerosols obtained in outdoor testing scenarios to a standard GC‐IMS biological aerosol dataset. The airflow improvement allowed more biomarker compounds to be observed in the GC‐IMS data domain for aerosols of gram‐negative Erwinia herbicola (EH) and ovalbumin protein as compared to previous studies. Minimal differences were observed for gram‐positive spores of Bacillus subtilis var. globigii (BG) from that of earlier work. Prior outdoor aerosol challenges dealt with the detection of one organism, either EH or BG. Biological aerosols were disseminated in a Western Canadian prairie and the Py‐GC‐IMS was tested for its ability to detect the biological aerosols. The current series of outdoor trials consisted of three different biological aerosol challenges. Forty‐two trials were conducted and a simple area calculation of the GC‐IMS data domain biomarker peaks correlated with the correct bioaerosol challenge in 30 trials (71%). In another 7 trials, the status of an aerosol was determined to be biological in origin. Two additional trials had no discernible, unambiguous GC‐IMS biological response, because they were blank water sprays. Reproducible limits of detection were at a concentration of less than 0.5 bacterial analyte‐containing particle per liter of air. In order to realize this low concentration, an aerosol concentrator was used to concentrate 2000 l of air in 2.2 min. Previous outdoor aerosol trials have shown the Py‐GC‐IMS device to be a credible detector with respect to determining the presence of a biological aerosol. The current series of outdoor trials has provided a platform to show that the Py‐GC‐IMS can provide information more specific than a biological or non‐biological analysis to an aerosol when the time of dissemination is unknown to the operator. The Py‐GC‐IMS is shown to be able to discriminate between aerosols of a gram‐positive spore (BG), a gram‐negative bacterium (EH), and a protein (ovalbumin). © 2001 John Wiley & Sons, Inc. Field Analyt Chem Technol 5: 190–204, 2001
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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 | 0.001 | 0.001 |
| 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 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".