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Record W4377020168 · doi:10.1016/j.ajhg.2023.04.010

Monoallelic intragenic POU3F2 variants lead to neurodevelopmental delay and hyperphagic obesity, confirming the gene’s candidacy in 6q16.1 deletions

2023· article· en· W4377020168 on OpenAlexaff
Ria Schönauer, Wenjun Jin, Christin Findeisen, Irene Valenzuela, Laura A. Devlin, Jill R. Murrell, Emma Bedoukian, Linda Pöschla, Elena Hantmann, Korbinian M. Riedhammer, Julia Hoefele, Konrad Platzer, Ronald Biemann, Philippe M. Campeau, Johannes Münch, Henrike Heyne, Anne Hoffmann, Adhideb Ghosh, Wenfei Sun, Hua Dong, Falko Noé, Christian Wolfrum, Emily Woods, Michael Parker, Ruxandra Neatu, Gwenaël Le Guyader, Ange‐Line Bruel, Laurence Perrin, H.L. Spiewak, Isabelle Missotte, Mélanie Fourgeaud, Vincent Michaud, Didier Lacombe, Sarah A Paolucci, Jillian G. Buchan, Margaret Glissmeyer, Bernt Popp, Matthias Blüher, John A. Sayer, Jan Halbritter

Bibliographic record

VenueThe American Journal of Human Genetics · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics and Neurodevelopmental Disorders
Canadian institutionsUniversité de Montréal
FundersMedical Research CouncilNorthern Counties Kidney Research FundNational Health Research InstitutesDeutsche ForschungsgemeinschaftCancer Research UKElse Kröner-Fresenius-StiftungNational Institute for Health and Care ResearchHeart of England NHS Foundation TrustDepartment of Health and Social CareNational Institutes of HealthKidney Research UKWellcome Trust
KeywordsGeneticsMissense mutationAutismObesityBiologyAutism spectrum disorderGeneNeurodevelopmental disorderBioinformaticsMedicineMutationEndocrinologyPsychiatry

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.015
GPT teacher head0.264
Teacher spread0.249 · 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

Citations8
Published2023
Admission routes1
Has abstractno

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