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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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.491
Threshold uncertainty score0.816

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.056
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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
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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