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Record W4413140527 · doi:10.1016/s2215-0366(25)00162-2

Holistic prevention and management of physical health side-effects of psychotropic medication: second report of the Lancet Psychiatry Physical Health Commission

2025· review· en· W4413140527 on OpenAlexaff
Sean Halstead, Chloe X. Yap, Nicola Warren, Sri Mahavir Agarwal, Bodyl A. Brand, Sherry Kit Wa Chan, Andrea Cipriani, Christoph U. Correll, Nicolás Crossley, Enrico D’Ambrosio, Robin Emsley, Joseph Firth, Fiona Gaughran, Siobhan Gee, Margaret Hahn, Joseph Hayes, Adrian Heald, Oliver Howes, John M. Kane, Maria Kapi, S. Leucht, Nicholas Meyer, Emmanuel Sunday Okeke, Benjamin I. Perry, Marco Solmi, I. Sommer, Vivek Srivastava, Heidi Taipale, David Taylor, Jari Tiihonen, Allan H. Young, Dan Siskind, Brian O’Donoghue, Toby Pillinger, Robert A. McCutcheon

Bibliographic record

VenueThe Lancet Psychiatry · 2025
Typereview
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsOttawa HospitalUniversity of TorontoCentre for Addiction and Mental Health
FundersNational Health Service CorpsWellcome TrustNIHR Oxford Biomedical Research CentreAcademy of Medical SciencesNational Health and Medical Research CouncilBrain and Behavior Research FoundationDepartment of Health and Social CareUK Research and InnovationNational Institute for Health and Care Research Applied Research Collaboration Oxford and Thames ValleyMaudsley CharityNational Institute for Health and Care ResearchUniversity College London
KeywordsCommissionPsychiatryPhysical healthMedicineAlternative medicineMental healthPsychologyPolitical science

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)0.005
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.011
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.056
GPT teacher head0.431
Teacher spread0.376 · 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 designNot applicable
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

Citations16
Published2025
Admission routes1
Has abstractno

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