Patterns and Transitions in Substance Use Among Young Swiss Men
Bibliographic record
Abstract
This study investigates the potential stages of drug use. Data from the longitudinal Cohort Study on Substance Use Risk Factors were used ( N = 5,116). Drug use (alcohol, tobacco, and 16 illicit drugs) over the previous 12 months was assessed at two time points. Patterns and trajectories of drug use were studied using latent transition analysis (LTA). This study’s substantive contributions are twofold. First, the pattern of drug use displayed the well-known sequence of drug involvement (licit drugs to cannabis to other illicit drugs), but with an added distinction between two kinds of illicit drugs (“middle-stage” drugs: uppers, hallucinogens, inhaled drugs; and “final-stage” drugs: heroin, ketamine, GHB/GBL, research chemicals, crystal meth, and spice). Second, subgroup membership was stable over time, as the most likely transition was remaining in the same latent class.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".