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Record W4400026233 · doi:10.17615/t1ae-0545

Classical Human Leukocyte Antigen Alleles and C4 Haplotypes Are Not Significantly Associated With Depression

2024· article· en· W4400026233 on OpenAlexfundno aff
Buttenschøn H.N, de Geus E.J.C, Jones L.A, Bertram Müller‐Myhsok, Lind P.A, Knowles J.A, Coleman J.R.I, Barbosa Gregory R, Van der Auwera S., Jack Euesden, Martin Preisig, Lucía Colodro‐Conde, Rudolf Uher, Shyn S.I., Penninx B.W.J.H., Ole Mors, Levinson D.F., Binder E.B, Udo Dannlowski, Potash J.B., Sara Mostafavi, Glyn Lewis, B I, Yuri Milaneschi, Hamilton S.P, Gerome Breen, Stephan Ripke, Ian Jones, Andlauer T.F.M, Neşe Direk, Jiawei Shi, Dunn E.C, Fabian Streit, Grabe H.J, Peter McGuffin, Weissman M.M., Sullivan P.F, Air T.M, Zoltán Kutalik, McIntosh A.M., Bissembayev A.T, Henning Tiemeier, Choi S.W, Purves K.L, Glanville K.P, Pedersen N.L., Susanne Lucae, Hanscombe K.B, Forstner A.J, Smoller J.W., M. K.

Bibliographic record

VenueUNC Libraries · 2024
Typearticle
Languageen
FieldNeuroscience
TopicTryptophan and brain disorders
Canadian institutionsnot available
FundersCilagNational Institute of Mental HealthNational Health and Medical Research CouncilStanley Center for Psychiatric Research, Broad InstituteUniversity of North Carolina at Chapel HillSchool of Medicine, Emory UniversityNational Institutes of HealthCentre for Cognitive Ageing and Cognitive EpidemiologyH. Lundbeck A/SMedical Research CouncilSiemens HealthineersInnovative Medicines InitiativeChinese Society of Clinical OncologyRheinische Friedrich-Wilhelms-Universität BonnUniversitair Medisch Centrum GroningenDokuz Eylül ÜniversitesiVetenskapsrådetGGZ DrenthePfizerRivierduinenGGZ inGeestDeutsche ForschungsgemeinschaftNederlandse Organisatie voor Wetenschappelijk OnderzoekBundesministerium für Bildung und ForschungErasmus Medisch CentrumVrije Universiteit AmsterdamKarolinska InstitutetZonMwKing's College LondonMax-Planck-GesellschaftRijksuniversiteit GroningenUniversiteit LeidenSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungNational Cancer InstituteUniversity College LondonLundbeckfondenKaiser PermanenteCardiff UniversityUniversität GreifswaldGGZ FrieslandPhilipps-Universität MarburgAarhus UniversitetUniversität BaselQIMR Berghofer Medical Research InstituteHøjteknologifondenLeids Universitair Medisch CentrumDepartment of Health and Social CareNational Institute for Health and Care ResearchAarhus UniversitetshospitalUniversity of Southern CaliforniaFoundation for the National Institutes of HealthBroad InstituteWellcome TrustWestfälische Wilhelms-Universität MünsterEmory UniversityNational Science FoundationMassachusetts General HospitalDalhousie UniversityGlaxoSmithKlineAstraZenecaUniversity of Worcester
KeywordsHaplotypeAlleleGeneticsDepression (economics)BiologyImmunologyGene

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.009
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0090.001

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 head0.035
GPT teacher head0.243
Teacher spread0.208 · 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 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

Citations0
Published2024
Admission routes1
Has abstractno

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