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Record W2890450469 · doi:10.1038/s41380-018-0247-6

Methylome-wide association findings for major depressive disorder overlap in blood and brain and replicate in independent brain samples

2018· article· en· W2890450469 on OpenAlexaff
Karolina A. Åberg, Brian Dean, Andrey A. Shabalin, Robin F. Chan, Laura K. M. Han, Min Zhao, Gerard van Grootheest, Lin Xie, Yuri Milaneschi, Shaunna L. Clark, Gustavo Turecki, Brenda W.J.H. Penninx, Edwin J. C. G. van den Oord

Bibliographic record

VenueMolecular Psychiatry · 2018
Typearticle
Languageen
FieldNeuroscience
TopicTryptophan and brain disorders
Canadian institutionsMcGill UniversityDouglas Mental Health University Institute
FundersNational Institute on Alcohol Abuse and AlcoholismNational Institute of Mental HealthMedical Research CouncilUniversitair Medisch Centrum GroningenNederlandse Organisatie voor Wetenschappelijk OnderzoekVrije Universiteit AmsterdamNational Institutes of HealthU.S. Department of Health and Human ServicesUniversiteit LeidenLeids Universitair Medisch Centrum
KeywordsReplicateMajor depressive disorderPsychologyAssociation (psychology)NeuroscienceDNA methylationSchizophrenia (object-oriented programming)PsychiatryBiologyGeneticsCognitionGenePsychotherapist

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)0.001
metaresearch head score (Gemma)0.004
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 score0.010
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.010
GPT teacher head0.262
Teacher spread0.252 · 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

Citations72
Published2018
Admission routes1
Has abstractno

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