Measurement of Hazardous Chemical Constituents and Mutagenic Activity in Fillers and Mainstream Smoke from Neo Cedar
Bibliographic record
Abstract
OBJECTIVE: To determine constituents of fillers and mainstream smoke from Neo Cedar. METHODS: Neo Cedar is a second-class over-the-counter (OTC) drug and similar to cigarettes in a number of ways. In particular, the design and usage are very similar to those of cigarettes. For the fillers of the drug, the levels of nicotine, tobacco-specific nitrosamines (TSNA), and heavy metals, and mutagenicity were determined using the methods for cigarette products. For the mainstream smoke, the levels of tar, nicotine, carbon monoxide (CO), TSNA, polycyclic aromatic hydrocarbons (PAH), and carbonyl compounds were also determined using the methods for cigarettes. The mainstream smoke from the drug were collected with a smoking machine using two smoking protocols (ISO and Health Canada Intense methods). RESULTS: The nicotine and total TSNA levels in the fillers of the drug averaged 2.86 mg/g and 185 ng/g, respectively. The nine species of heavy metals were also detected in the fillers of the drug. The levels of nicotine, tar, CO, TSNA, PAH, and carbonyl compounds of mainstream smoke from the drug were higher when determined using the HCI regime than when using the ISO regime. The mutagenicity of the mainstream smoke determined using the HCI regime was also higher than that determined using the ISO regime. CONCLUSION: In this study, all constituents of Neo Cedar were determined by methods for cigarette products. The drug had a ventilation hole on its filter. Thus, its constituents are different from those determined by the smoking protocols. Neo Cedar users should be careful of higher exposure to the hazardous gases owing to smoking patterns.
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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 | 0.001 | 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".