Selected Phenolic Compounds in Mainstream Cigarette Smoke, CORESTA Collaborative Study and Recommended Method *
Bibliographic record
Abstract
SUMMARY A collaborative study among 20 participating laboratories was conducted in an effort to publish a recommended method for determination of phenols in mainstream cigarette smoke. The study was conducted using 10 test samples including reference cigarettes and commercial products from various regions (ISO 3308 total particulate matter 1–16 mg/cig) smoked under two regimes (ISO 3308 and ISO 20778). Health Canada method T-114 was chosen as a basis for the analytical methodology and therefore mainstream cigarette smoke was trapped on 44-mm glass fiber filter pads which were subsequently extracted with 1% aqueous acetic acid for analysis by high performance liquid chromatography with fluorescence detection. Statistical analysis was carried out following ISO 5725 to generate repeatability (r) and reproducibility (R) data for results from linear and rotary smoking. For reproducibility (R) expressed as a percentage of mean yield across all of the studied products and both smoking regimes, values ranged from 17–150%. The lowest “tar” yielding products had the most variable data. Results trended as expected for total particulate matter, blend type, regime, and relative analyte yields. Results supporting a robust method for hydroquinone, resorcinol, catechol, phenol, o -cresol, m -cresol, and p -cresol are reported herein and support establishment of CRM 78, ISO 23904 and ISO 23905 standardized methods. [Contrib. Tob. Nicotine Res. 32 (2023) 18–25]
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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 | 0.057 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.002 | 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".