A Screening Method by Gas Chromatography-Mass Spectrometry for the Quantification of 24 Aerosol Constituents from Heat-Not-Burn Tobacco Products
Bibliographic record
Abstract
Summary A screening method allowing the quantification of 24 aerosol constituents using gas chromatography-mass spectrometry has been developed to assess the aerosol chemistry of heat-not-burn tobacco products. The aim of this method was to quantify phenol, o -cresol, m -cresol, p -cresol, catechol, resorcinol, hydroquinone, 1,3-butadiene, isoprene, benzene, acrylonitrile, toluene, pyridine, styrene, 1,2-propylene glycol, menthol, 2-furanmethanol, acrylamide, naphthalene, nicotine, acetamide, quinoline, triacetin, and glycerine in the aerosol emitted by heated tobacco products. The aerosol was generated by an electrically heated tobacco system (PMI’s Heated Tobacco System (THS 2.4)) with one single aerosol collection method, using the Health Canada smoking regimen and analyzed with two analytical methods. The method was validated according to the International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use and the Association of Official Analytical Chemists guidelines. A regression model based on a linear relationship between concentration and response ratio with a 1/x weighting factor was selected for phenol, o -cresol, m -cresol, p -cresol, 1,3-butadiene, isoprene, benzene, acrylonitrile, toluene, pyridine, styrene, 2-furanmethanol, acrylamide, naphthalene and acetamide. A quadratic regression model with a 1/x weighting factor was chosen for catechol, resorcinol, hydroquinone, 1,2-propylene glycol, menthol, nicotine, quinoline, triacetin and glycerine. Coefficients of variation for repeatability were determined between 7.9% and 17.8% and for intermediate precision between 8.1% and 19.9%. The matrix effect of the heated tobacco aerosol extract was assessed by performing a recovery study, where the aerosol extracts were spiked at different concentrations for the compounds to be analyzed. In addition, the mainstream smoke from 3R4F reference cigarettes was analyzed, and results were compared with previously published studies. The method was successfully validated, providing data consistent with published data and it was shown to be selective, precise and accurate.
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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".