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Record W2584004284 · doi:10.1016/j.pnpbp.2017.01.011

Pharmacogenetics of antidepressant response: A polygenic approach

2017· article· en· W2584004284 on OpenAlexaff
Judit García‐González, Katherine E. Tansey, Joanna Hauser, Neven Henigsberg, Wolfgang Maier, Ole Mors, Anna Placentino, Marcella Rietschel, Daniel Souery, Tina Žagar, Piotr M. Czerski, Borut Jerman, Henriette N. Buttenschøn, Thomas G. Schulze, Astrid Zobel, Anne Farmer, Katherine J. Aitchison, Ian Craig, Peter McGuffin, Michel Giupponi, Nader Perroud, Guido Bondolfi, David M. Evans, Michael O‘Donovan, T. J. Peters, Jens R. Wendland, Glyn Lewis, Shitij Kapur, Roy H. Perlis, Volker Arolt, Katharina Domschke, Gerome Breen, Charles Curtis, Lee Sang-Hyuk, Carol Kan, Stephen Newhouse, Hamel Patel, Bernhard T. Baune, Rudolf Uher, Cathryn M. Lewis, Chiara Fabbri

Bibliographic record

VenueProgress in Neuro-Psychopharmacology and Biological Psychiatry · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Associations and Epidemiology
Canadian institutionsDalhousie UniversityUniversity of Alberta
FundersNational Institute of Mental HealthEuropean Federation of Pharmaceutical Industries and AssociationsSeventh Framework ProgrammeNational Institutes of HealthLundbeckfondenEuropean CommissionKing's College LondonNational Institute for Health and Care ResearchMedical Research CouncilSixth Framework ProgrammeMenzies Centre for Australian Studies, King's College London, University of LondonSouth London and Maudsley NHS Foundation Trust
KeywordsPharmacogeneticsAntidepressantPolygenic risk scoreDrug responseMedicinePharmacologyComputational biologyPsychologyBiologyPsychiatryGeneticsGenotypeDrugSingle-nucleotide polymorphismGene

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationalhigh
models agreeAgreement compares identical category sets and study designs across arms.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.875

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.027
GPT teacher head0.347
Teacher spread0.320 · 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

Labeled directly by 2 models reading the full record.

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

Citations95
Published2017
Admission routes1
Has abstractno

Explore more

Same venueProgress in Neuro-Psychopharmacology and Biological PsychiatrySame topicGenetic Associations and EpidemiologyFrench-language works237,207