Online Comprehensive Two-Dimensional Characterization of Puff-by-Puff Resolved Cigarette Smoke by Hyphenation of Fast Gas Chromatography to Single-Photon Ionization Time-of-Flight Mass Spectrometry: Quantification of Hazardous Volatile Organic Compounds
Bibliographic record
Abstract
This work presents the direct coupling of a custom-made smoking machine (SM) to fast gas chromatography combined with single-photon ionization mass spectrometry (GC × SPI-MS) utilizing a six-port, two-position valve for online puff-resolved comprehensive two-dimensional investigation of cigarette smoke. The innovative electron-beam pumped rare gas excimer light source (EBEL) filled with argon provided vacuum ultraviolet (VUV) photons of 9.8 ± 0.4 eV (126 ± 9 nm) for SPI. Puff-by-puff quantification of 14 hazardous volatile organic smoke constituents from the 2R4F Kentucky research cigarette was enabled for two smoking regimes, i.e., ISO and Canadian Intense, after determination of photoionization cross sections. The investigated analytes comprised NO, acetaldehyde, butadiene, acrolein, propanal, acetone, isoprene, furan, crotonaldehyde, isobutanal, butanal, 2-butanone, benzene, and toluene. The determined amounts of these compounds in cigarette smoke agreed excellently with the literature values. Furthermore, the two well-known patterns of puff-by-puff behaviors for these different smoke constituents were obtained for both whole smoke and gas-phase measurements.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".