The Effects of Alcohol on Responses to Nicotine‐Containing and Denicotinized Cigarettes in Dependent and Nondaily Smokers
Bibliographic record
Abstract
BACKGROUND: Alcohol consumption has been linked to increased tobacco use and craving in both dependent and nondaily smokers, yet the extent to which these relationships depend on interactions involving nicotine remains unclear. This study examined the acute effects of alcohol on the subjective and behavioral responses to nicotine-containing tobacco and denicotinized tobacco in 17 (10 male) dependent daily smokers (DDS) and 23 (11 male) nondependent nondaily smokers (NNS). METHODS: During 4 randomized double-blind sessions, participants assessed the effects of nicotine-containing tobacco or denicotinized tobacco following the administration of a moderately intoxicating dose of alcohol (mean blood alcohol concentration = 0.076 g/dl) or a placebo beverage. They could then self-administer additional puffs of the same type of cigarette sampled over a 60-minute period using a progressive ratio task. RESULTS: In NNS, alcohol significantly increased the self-administration of both nicotine-containing and denicotinized cigarettes, and no differences in self-administration were observed between the 2 types of tobacco within either beverage condition. In contrast, in DDS, alcohol was associated with decreased denicotinized tobacco self-administration relative to the placebo beverage condition as well as with increased self-administration of nicotine-containing tobacco relative to denicotinized tobacco. DDS also exhibited relatively elevated craving following the administration of a nicotine-containing cigarette in the alcohol beverage condition. CONCLUSIONS: Findings suggest that nicotine may be critical to the drinking-smoking relationship in DDS, but that nonnicotine smoking factors may be more important in NNS.
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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 | 0.001 |
| 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) | 0.001 | 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".