Smoking Topography, Brand Switching, and Nicotine Delivery: Results from an <i>In vivo</i> Study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: Exposure to toxins in tobacco smoke is influenced by how a cigarette is smoked. Cigarettes have been designed to allow for a range of puffing behavior and to provide different, nonlinear tar and nicotine yields in response to different puffing profiles. However, puffing behavior and its influence upon risk-exposure has yet to be assessed outside the laboratory, in smokers' natural environment. METHOD: Fifty-nine adult smokers used a portable device to measure smoking topography over the course of three 1-week trials. Participants were asked to smoke their usual "regular yield" brand through the device for trial 1 and again, 6 weeks later, at trial 2. Half the subjects were then randomly assigned to switch to a "low-yield" brand for trial 3. RESULTS: The findings show a high degree of stability in puffing behavior within the same subject over time but considerable variability between smokers. Smokers who were switched to a "low-yield" cigarette increased their total smoke intake per cigarette by 40% (P = 0.007), with no significant change in their salivary cotinine levels. Cigarettes smoked per day and nicotine yield were only weakly associated with salivary cotinine levels; however, salivary cotinine was strongly associated with a composite measure that included cigarettes per day, brand elasticity, and puffing behavior (sr = 0.61, P < 0.001). CONCLUSIONS: These findings provide strong evidence of behavioral compensation to low-yield cigarettes from in vivo measures of smoking behavior. The findings also show the importance of brand elasticity and smoking topography in predicting nicotine uptake and smoke exposure.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it