Determination of Polycyclic Aromatic Hydrocarbons in Cigarettes and Cigarette Smoke
Bibliographic record
Abstract
The present study examines the concentrations of polycyclic aromatic hydrocarbons (PAHs) in cigarettes and sidestream cigarette smoke. Nine PAHs were determined in sidestream cigarette smokes for five types of cigarettes. The volume of the experimental room is approximately 66 m3. The air samples in the room were collected before and after smoking. The total PAH concentrations were approximately 1.0 ng/m3 before smoking, but the median concentration and the range of PAHs were 29.1 ng/m3 and from 7.62 to 57.6 ng/m3 after smoking. The relationship between suspended particulate matter (SPM) and total PAHs after smoking is significant and proportional. This may indicate that the SPM formation is associated with PAH formation during smoking. Furthermore, nine PAHs were determined in the cigarettes. Median PAH contents in the five brands of cigarettes ranged from 221 to 936 ng per cigarette before smoking and from 66.9 to 266 ng per cigarette after smoking. Mean PAH emissions from cigarettes while smoking ranged from 257 to 1490 ng per cigarette. The results show that PAHs in the cigarettes, and those generated during smoking, were emitted into the air.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".