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Rare coding variants in genes encoding GABAA receptors in genetic generalised epilepsies: an exome-based case-control study
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
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 distilled prediction
Teacher imitationNot 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 score0.012
Threshold uncertainty score0.638
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 head0.060
GPT teacher head0.331
Teacher spread0.271 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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