Atmospheric pressure chemical ionization mass spectrometry of pyridine and isoprene: potential breath exposure and disease biomarkers
Bibliographic record
Abstract
Volatile organic compounds (VOCs) in exhaled human breath can serve as potential disease-specific and exposure biomarkers and therefore can reveal information about a subject's health and environment. Pyridine, a VOC marker for exposure to tobacco smoke, and isoprene, a liver disease biomarker, were studied using atmospheric pressure chemical ionization mass spectrometry (APCI-MS). While both molecules could be detected in low-ppb levels, interactions of the ionized analytes with their neutral forms and ambient air led to unusual ion/molecule chemistry. The result was a highly dynamic system and a nonlinear response to changes in analyte concentration. Increased presence of ambient water was found to greatly enhance the detection limit of pyridine and only slightly decrease that of isoprene. APCI-MS is shown to be a promising analytical tool in breath analysis with good detection limits, but its application requires a better understanding of the ion/molecule chemistry that may affect VOC quantification from a chemically complex system such as human breath.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".