Comparison of 3R4F cigarette smoke and IQOS heated tobacco product aerosol emissions
Bibliographic record
Abstract
In this study, the smoke from a 3R4F research cigarette and the aerosol generated by the Heated Tobacco Product IQOS, also referred to as the Tobacco Heating System (THS) 2.2 in the literature, were compared. The objective was to characterize the gas and suspended particulate matter compositions in the mainstream smoke from a combusted 3R4F cigarette and in the aerosol generated by IQOS during use. The results indicated that the determined aerosol emissions from IQOS were notably lower than in the cigarette smoke under a Health Canada Intense puffing regimen. As an interesting detail in this study, the maximum nicotine concentrations within a puff were practically the same in both the 3R4F smoke and the IQOS aerosol, but the average concentration was lower for the IQOS aerosol. For both products, water constituted a significant proportion of the particulate matter, although it was substantially higher in the IQOS aerosol. Furthermore, combustion-related solid particles observed in the 3R4F smoke contained elements such as carbon, oxygen, potassium, calcium, and silicon. In contrast, IQOS aerosol particulate matter was composed of semi-volatile organic constituents with some minor traces of oxygen and silicon. The particulate matter found in the IQOS aerosol was volatile, which was especially noticeable when exposed to the electron beam of the scanning electron microscope (SEM) and Transmission Electron Microscope (TEM).
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".