Gas Chromatography-Tandem Mass Spectrometry Method for Selective Detection of 2-Nitropropane in Mainstream Cigarette Smoke
Bibliographic record
Abstract
Although 2-nitropropane is a potentially harmful compound present in cigarette smoke, there are few fully-validated, modern methods to quantitate it in mainstream cigarette smoke. We developed an isotope dilution gas chromatography-tandem mass spectrometry (ID-GC-MS/MS) method for the detection of 2-nitropropane in mainstream cigarette smoke. The vapor fraction of mainstream cigarette smoke was collected in inert polyvinyl fluoride gas sampling bags and extracted with hexanes containing isotopically labeled internal standard, then purified and concentrated via solid-phase extraction using a normal phase silica adsorbent and a 100% dichloromethane eluant. This method is sensitive enough to measure vapor phase 2-nitropropane concentrations in the nanogram range, with a 19 ng per cigarette method limit of detection. Product variability estimated from the analysis of 15 cigarette products yielded relative standard deviations ranging from 5.4% to 15.7%, and estimates of precision from two quality control products yielded relative standard deviations of 9.49% and 14.9%. Under the Health Canada Intense smoking regimen, 2-nitropropane in machine-generated mainstream smoke from 15 cigarette products ranged from 98.3 to 363 ng per cigarette.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".