The impact of learning of a genetic predisposition to nicotine dependence: an analogue study: Table 1
Bibliographic record
Abstract
OBJECTIVES: To examine the consequences of informing smokers of a genetic predisposition to nicotine dependence and of providing treatment efficacy information tailored to genetic status. DESIGN: Analogue study using four vignettes; 2 (genetic status) x 2 (whether treatment efficacy information provided) between subjects design. PARTICIPANTS: 269 British adult smokers. OUTCOME MEASURES: Preferred cessation methods and perceived control over quitting. RESULTS: Gene positive participants were significantly more likely to choose the cessation method described as effective for their genetic status, but significantly less likely to choose to use their own willpower. Providing tailored treatment information did not alter these effects. Perceived control was not significantly affected by either genetic status or information provision. CONCLUSIONS: Learning of a genetic predisposition to nicotine dependence may increase desire for effective cessation methods, but may undermine the perceived importance of willpower in stopping smoking.
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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 | 0.010 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".