Evidence for clinicians: Atypical antipsychotics for disruptive behaviour disorders in children and youths
Bibliographic record
Abstract
For the current issue of the Journal, we asked Dr. Iliana Ortega to comment on and put into context the recent Cochrane Review on atypical antipsychotics for disruptive behaviour disorders (DBD). This is an update of the original Cochrane Review, last published in 2012 (1). Children and youths with DBD may present to health services, where they may be treated with atypical antipsychotics. There is increasing usage of atypical antipsychotics in the treatment of DBD. The objective of this study was to evaluate the effect and safety of atypical antipsychotics, compared to placebo, for treating DBD in children and youths. The aim was to evaluate each drug separately rather than the class effect, on the grounds that each atypical antipsychotic has a different pharmacologic binding profile (2) and that this is clinically more useful. In January 2017, we searched CENTRAL, MEDLINE, Embase, five other databases, and two trials registers.
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 | 0.024 | 0.183 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.009 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.012 | 0.006 |
| Insufficient payload (model declined to judge) | 0.016 | 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".