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Record W4402088096 · doi:10.1038/s41398-024-03064-x

Correction: Metabolic activity of CYP2C19 and CYP2D6 on antidepressant response from 13 clinical studies using genotype imputation: a meta-analysis

2024· erratum· en· W4402088096 on OpenAlexaff
Danyang Li, Oliver Pain, Chiara Fabbri, Win Lee Edwin Wong, Chris Wai Hang Lo, Stephan Ripke, Annamaria Cattaneo, Daniel Souery, Mojca Zvezdana Dernovšek, Neven Henigsberg, Joanna Hauser, Glyn Lewis, Ole Mors, Nader Perroud, Marcella Rietschel, Rudolf Uher, Wolfgang Maier, Bernhard T. Baune, Joanna M. Biernacka, Guido Bondolfi, Katharina Domschke, Masaki Kato, Yu‐Li Liu, Alessandro Serretti, Shih‐Jen Tsai, Richard M. Weinshilboum, Andrew M. McIntosh, Cathryn M. Lewis

Bibliographic record

VenueTranslational Psychiatry · 2024
Typeerratum
Languageen
FieldMedicine
TopicDiet and metabolism studies
Canadian institutionsDalhousie University
FundersNational Institute of Mental HealthMedical Research CouncilH. Lundbeck A/SJapanese Society of Clinical NeuropsychopharmacologyServierShionogiSENSHIN Medical Research FoundationEli Lilly and CompanyOno PharmaceuticalEisaiKing's College LondonNational Institute for Health and Care ResearchJapan Research Foundation for Clinical PharmacologyBristol-Myers SquibbAstraZenecaItalfarmacoMitsubishi Tanabe Pharma CorporationWellcome TrustF. Hoffmann-La RocheEuropean Federation of Pharmaceutical Industries and AssociationsEuropean CommissionSanofiNIHR Maudsley Biomedical Research CentreJapan Society for the Promotion of ScienceGlaxoSmithKlinePfizer
KeywordsCYP2C19CYP2D6AntidepressantMeta-analysisImputation (statistics)PsychologyGenotypeMedicinePharmacogeneticsPharmacologyClinical psychologyPsychiatryInternal medicineBiologyGeneticsStatisticsMathematicsMissing data

Abstract

fetched live from OpenAlex

In this article the author’s name Chiara Fabbri was incorrectly written as Fabbri Chiara. The original article has been corrected.

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 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)0.016
metaresearch head score (Gemma)0.196
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.075
Threshold uncertainty score0.251

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.196
Meta-epidemiology (narrow)0.0040.002
Meta-epidemiology (broad)0.0030.004
Bibliometrics0.0050.007
Science and technology studies0.0020.002
Scholarly communication0.0040.002
Open science0.0040.002
Research integrity0.0040.009
Insufficient payload (model declined to judge)0.0750.024

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 head0.145
GPT teacher head0.426
Teacher spread0.281 · 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
GenreEmpirical

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

Citations2
Published2024
Admission routes1
Has abstractyes

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