The Effects of Filter Ventilation and Expanded Tobacco on the Tar, Nicotine and Carbon Monoxide Yields from Cigarettes Sold in Australia
Bibliographic record
Abstract
Cigarette brand variant names and characteristics such as the taste and feel of the smoke can mislead consumers into believing some products are less harmful. We assessed the characteristics of three common cigarette variants sold in Australia, "gold", "blue" and "red", to determine which characteristics differed by color, and which affected tar, nicotine and carbon monoxide (TNCO) yields. TNCO yields, physical parameters, expanded tobacco and filter ventilation were measured in cigarette color variants from eight brands. Filter ventilation and expanded tobacco were common across brands and variants. Compared to blue and red variants, gold variants had slightly shorter tobacco rods and greater filter ventilation. Gold variants had lower TNCO when measured using the industry-favored International Organization for Standardization (ISO) protocol. ISO-measured TNCO yields were associated with filter ventilation and tobacco rod length, but not use of expanded tobacco. When measured using the Health Canada Intensive (HCI) protocol, which better emulates human smoking behavior, TNCO emissions were markedly higher, and the emission differences by extent of filter ventilation were minimized, indicating that ISO measurements are misleading. These findings confirm that cigarette color names, and the filter ventilation levels they signify, remain misleading more than a decade after plain packaging eliminated pack colors in Australia, as higher levels of filter ventilation are not associated with reduced TNCO emissions measured using the HCI protocol. Consumer education and communication campaigns could amplify the impacts of Australia's newly passed tobacco legislation banning color and other variant names that imply reduced harm.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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".