A modified trapping method to quantify hydrogen cyanide in mainstream and sidestream cigarette smoke under ISO and Health Canada intense smoking regimes
Bibliographic record
Abstract
Hydrogen cyanide is a toxic compound and plays a critical role in cigarette smoke hazard assessment. Due to its reactivity with other chemicals of cigarette smoke, hydrogen cyanide collection was accomplished by the novel trapping method established in our laboratory using glass-fibre filter pads (GFP) treated by sodium hydroxide. However, the GFP trapping method has not been tested under Health Canada Intense (HCI) smoking regime and the trapping efficiency of GFP versus traditional methods have not been evaluated. The present study employed the two trapping methods to collect hydrogen cyanide in mainstream and sidestream cigarette smoke under ISO and HCI smoking regimes. The causes leading to losses of hydrogen cyanide and effects of smoking parameters used in the traditional trapping method were also investigated in this study. It was found that under both ISO and HCI smoking regimes the amounts of hydrogen cyanide in GFP trapping method were strongly correlated (r>0.99) with those by the traditional trapping method, though the traditional method trapped less hydrogen cyanide in sidestream smoke. Carbonyl compounds, such as formaldehyde, were identified as the contributors for the loss of hydrogen cyanide in the alkaline solution. Puff profile was affected to some extents by the use of impinger. Collectively, the results indicate that the modified trapping method is preferred for the routine analysis of hydrogen cyanide in cigarette smoke under ISO and HCI smoking regimes.
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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) | 0.000 | 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) | 0.001 | 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".