Examining the Nature of the Association between Attention-Deficit Hyperactivity Disorder and Nicotine Dependence: A Familial Risk Analysis
Bibliographic record
Abstract
OBJECTIVE: To use familial risk analysis to examine the association between attention-deficit hyperactivity disorder (ADHD) and nicotine dependence (ND). METHOD: Subjects were children with (n = 257) and without (n = 229) ADHD of both sexes ascertained from pediatric and psychiatric referral sources and their first-degree relatives (N = 1627). RESULTS: ND in probands increased the risk for ND in relatives irrespective of ADHD status. There was no evidence of cosegregation or assortative mating between these disorders. Patterns of familial risk analysis suggest that the association between ADHD and ND is most consistent with the hypothesis of independent transmission of these disorders. CONCLUSIONS: These findings may have important implications for the identification of a subgroup of children with ADHD at high risk for ND based on parental history of ND.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".