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Record W2883808148 · doi:10.1016/s1474-4422(18)30215-1

Rare coding variants in genes encoding GABAA receptors in genetic generalised epilepsies: an exome-based case-control study

2018· article· en· W2883808148 on OpenAlexaff
Patrick May, Simon Girard, Merle Harrer, Dheeraj Reddy Bobbili, Julian Schubert, Stefan Wolking, Pamela Lachance‐Touchette, Caroline Meloche, Cristina Elena Niturad, Julia Knaus, Carolien G. F. de Kovel, Mohamad Toliat, Michele Iacomino, Rosa Guerrero, Stéphanie Baulac, Carla Marini, Holger Thiele, Kamel Jabbari, Ann‐Kathrin Ruppert, Dennis Lal, Christopher A. Reid, Hande Çağlayan, Kate V. Everett, Hiltrud Muhle, Ingo Helbig, Wolfram S. Kunz, Yvonne Weber, Sarah Weckhuysen, Peter De Jonghe, Sanjay M. Sisodiya, Antonietta Coppola, Maria Stella Vari, Uğur Özbek, Karl Martin Klein, Dang Khoa Nguyen, Anne Lortie, Richard Desbiens, Cécile Cieuta‐Walti, Graeme J. Sills, Pauls Auce, Ben Francis, Michael R. Johnson, Anthony G Marson, Josemir W. Sander, Andreja Avberšek, Mark McCormack, Gianpiero L. Cavalleri, Norman Delanty, Martin Krenn, Fritz Zimprich, Sarah Peter, Marina Nikanorova, Robert Kraaij, Jeroen van Rooij, Rudi Balling, M. Arfan Ikram, André G. Uitterlinden, Stéphanie Schorge, Massimo Mantegazza, Éric Leguern, José M. Serratosa, Anna‐Elina Lehesjoki, Michael Nothnagel, Peter Nürnberg, Federico Zara, Patrick Cossette, Holger Lerche, Edoardo Ferlazzo, Carlo Di Bonaventura, Angela La Neve, Paolo Tinuper, Francesca Bisulli, Aglaia Vignoli, Giuseppe Capovilla, Giovanni Crichiutti, Antonio Gambardella, Vincenzo Belcastro, Amedeo Bianchi, Destînâ Yalçın, Gülşen Dizdarer, Kezban Arslan, Zühal Yapıcı, Demet Yandım Kuşçu, Costin Leu, Kristin Heggeli, Joseph Willis, Sarah R. Langley, Andrea Jorgensen, Prashant K. Srivastava, Sarah Rau, Christian Hengsbach, Anja C. M. Sonsma

Bibliographic record

VenueThe Lancet Neurology · 2018
Typearticle
Languageen
FieldMedicine
TopicEpilepsy research and treatment
Canadian institutionsCentre Hospitalier de l’Université de MontréalUniversité de SherbrookeUniversité de Montréal
FundersEuropean Social FundMedical Research CouncilEpilepsy SocietyDesitin ArzneimittelFachagentur Nachwachsende RohstoffeTechnische Universität MünchenTürkiye Bilimsel ve Teknolojik Araştırma KurumuEisaiMinistry of Science, ICT and Future PlanningSixth Framework ProgrammeHessisches Ministerium für Wissenschaft und KunstNagao Natural Environment FoundationNederlandse Organisatie voor Wetenschappelijk OnderzoekUniversité du LuxembourgMinisterie van Onderwijs, Cultuur en WetenschapAcademy of FinlandZonMwUniversity College London Hospitals NHS Foundation TrustErasmus Universiteit RotterdamScience Foundation IrelandDeutsche ForschungsgemeinschaftMarie CurieEuropean Science FoundationWellcome TrustWorld Health OrganizationUniversity College LondonRoyal SocietyBundesministerium für Bildung und ForschungNational Institute for Health and Care ResearchDeutsche Gesellschaft für EpileptologieEU Joint Programme – Neurodegenerative Disease ResearchSeventh Framework ProgrammeMinisterio de Ciencia, Innovación y UniversidadesMinisterie van Volksgezondheid, Welzijn en SportUCBErasmus Medisch CentrumGlaxoSmithKlineEuropean CommissionDanish Cancer Society Research Center
KeywordsGABAA receptorExome sequencingGeneGeneticsExomeCoding (social sciences)BiologyReceptorComputational biologyMutationMathematics

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 score0.005
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.060
GPT teacher head0.331
Teacher spread0.271 · 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

Citations93
Published2018
Admission routes1
Has abstractno

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