Pathways to Psychosis in Cannabis Abuse
Bibliographic record
Abstract
Cannabis has been implicated as a risk factor for the development of schizophrenia, but the exact biological mechanisms remain unclear. In this review, we attempt to understand the neurobiological pathways that link cannabis use to schizophrenia. This has been an area of great debate; despite similarities between cannabis users and schizophrenia patients, the evidence is not sufficient to establish cause-and-effect. There have been advances in the understanding of the mechanisms of cannabis dependence as well as the role of the cannabinoid system in the development of psychosis and schizophrenia. The neurobiological mechanisms associated with the development of psychosis and effects from cannabis use may be similar but remain elusive. In order to better understand these associations, this paper will show common neurobiological and neuroanatomical changes as well as common cognitive dysfunction in cannabis users and patients of schizophrenia. We conclude that epidemiologic evidence highlights potential causal links; however, neurobiological evidence for causality remains weak.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".