Bibliographic record
Abstract
This commentary deals with our publication from 12.2024, entitled “Early Detection and Treatment Options for Psychosis in Transition from Childhood to Adolescence: A Review About Three Decades of Psychiatric Clinical Experience” [1]. The article delves into the complex relationship between substance abuse and psychosis, focusing on the critical role of early detection, family involvement, and continuous monitoring in managing psychosis, particularly during the transition from childhood to adolescence. It highlights the impact of substance abuse on the onset and progression of psychosis, the importance of tools like OPATUS CPTA in diagnosis and treatment, and the challenges faced during the transition from child to adult psychiatry. We discuss findings from various studies on cannabis-related disorders and the genetic heritability of schizophrenia, emphasizing the need for comprehensive strategies to address these issues. In this commentary, we include a case report from 2022 [2], showing the importance of differential diagnosis between drug-related and nondrug-related psychosis and add a new Canadian study, published in 2025 with new data on how incidence rates for psychosis have gone up after legalization of cannabis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.011 | 0.009 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".