Cannabis use increases the risk of young people developing psychotic symptoms, particularly if already predisposed
Bibliographic record
Abstract
Henquet C, Krabbendam L, Spauwen J, et al . Prospective cohort study of cannabis use, predisposition for psychosis, and psychotic symptoms in young people. BMJ 2004;330:11–14. Q Does cannabis use increase the risk of developing psychotic symptoms in young people with or without a predisposition for psychosis? ### ![Graphic][1]</img>Design: Prospective cohort study. ### ![Graphic][2]</img>Follow up period: Four years. ### ![Graphic][3]</img>Setting: The city and counties of Munich, Germany ### ![Graphic][4]</img>People: 2437 young people aged 14–24 years with or without a predisposition for psychosis and born between 1 June 1970 and 31 May 1981. ### ![Graphic][5]</img>Risk factors: Participants were assessed for cannabis use and for psychosis and predisposition to psychosis by the Munich version of the composite international diagnostic interview (M-CIDI), at baseline and four years follow up. Logistic regression was used to calculate odds ratios and … [1]: /embed/inline-graphic-1.gif [2]: /embed/inline-graphic-2.gif [3]: /embed/inline-graphic-3.gif [4]: /embed/inline-graphic-4.gif [5]: /embed/inline-graphic-5.gif
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How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".