MétaCan
Menu
Back to cohort
Record W4399453190 · doi:10.1016/j.schres.2024.05.020

The effect of second-generation antipsychotics on anxiety/depression in patients with schizophrenia: A systematic review and meta-analysis

2024· review· en· W4399453190 on OpenAlexafffund
Ali Abdolizadeh, Maryam Hosseini Kupaei, Yasaman Kambari, Aron Amaev, Vittal Korann, Edgardo Torres‐Carmona, Jianmeng Song, Fumihiko Ueno, M KOIZUMI, Shinichiro Nakajima, Sri Mahavir Agarwal, Philip Gerretsen, Ariel Graff-Guerrero

Bibliographic record

VenueSchizophrenia Research · 2024
Typereview
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental Health
FundersBanting and Best Diabetes Centre, University of TorontoDepartment of Psychiatry, University of TorontoJapan Society for the Promotion of ScienceOntario Ministry of Health and Long-Term CareUniversity of TorontoMinistry of Training, Colleges and UniversitiesCanadian Institutes of Health ResearchCentre for Addiction and Mental Health FoundationPhysicians' Services Incorporated FoundationCentre for Addiction and Mental HealthUehara Memorial FoundationJapan Agency for Medical Research and DevelopmentNakatani Foundation for Advancement of Measuring Technologies in Biomedical EngineeringJapanese Society of Clinical NeuropsychopharmacologyJapan Research Foundation for Clinical PharmacologyWatanabe FoundationTakeda Science FoundationMeso Scale DiagnosticsBrain and Behavior Research FoundationNaito FoundationDiscovery Eye Foundation
KeywordsSchizophrenia (object-oriented programming)AnxietyMeta-analysisDepression (economics)PsychiatryGuidelineClozapineClinical psychologyMedicinePsychologyInternal medicine

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.017
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.012
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0170.030
Bibliometrics0.0040.004
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.074
GPT teacher head0.400
Teacher spread0.326 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

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".

Quick stats

Citations10
Published2024
Admission routes2
Has abstractno

Explore more

Same venueSchizophrenia ResearchSame topicSchizophrenia research and treatmentFrench-language works237,207