A Comparison between Cigarette Topography from a One-Week Natural Environment Study to FTC/ISO, Health Canada, and Massachusetts Department of Public Health Puff Profile Standards
Bibliographic record
Abstract
Standardized topography protocols for testing cigarette emissions include the Federal Trade Commission/International Standard Organization (FTC/ISO), the Massachusetts Department of Health (MDPH), and Health Canada (HC). Data are lacking for how well these protocols represent actual use behavior. This study aims to compare puff protocol standards to actual use topography measured in natural environments across a range of cigarette brands. Current smokers between 18 and 65 years of age were recruited. Each participant was provided with a wPUM™ cigarette topography monitor and instructed to use the monitor with their usual brand cigarette ad libitum in their natural environment for one week. Monitors were tested for repeatability, and data were checked for quality and analyzed with the TAP™ topography analysis program. Data from n = 26 participants were analyzed. Puff flow rates ranged from 17.2 to 110.6 mL/s, with a mean (STD) of 40.4 (21.7) mL/s; durations from 0.7 to 3.1 s, with a mean (STD) of 1.5 ± 0.5 s; and volumes from 21.4 to 159.2 mL, with a mean (STD) of 54.9 (29.8) mL. Current topography standards were found to be insufficient to represent smoking across the wide range of real behaviors. These data suggest updated standards are needed such that emissions tests will provide meaningful risk assessments.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".