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NEK1 variants confer susceptibility to amyotrophic lateral sclerosis
Kevin P. Kenna, Perry T.C. van Doormaal, Annelot M. Dekker, Nicola Ticozzi, Brendan Kenna, Frank P. Diekstra, Wouter van Rheenen, Kristel R. van Eijk, Pamela Keagle, Aleksey Shatunov, William Sproviero, Bradley Smith, Michael A. van Es, Simon Topp, Aoife Kenna, Jack W. Miller, Claudia Fallini, Cinzia Tiloca, Russell L. McLaughlin, Caroline Vance, Claire Troakes, Claudia Colombrita, Gabriele Mora, Andrea Calvo, Federico Verde, Safa Al‐Sarraj, Andrew King, Daniela Calini, Jacqueline de Belleroche, Frank Baas, Anneke J. van der Kooi, Marianne de Visser, Anneloor L.M.A. ten Asbroek, Peter C. Sapp, Diane McKenna‐Yasek, Meraida Polak, José Luís Muñoz-Blanco, Tim M. Strom, Thomas Meitinger, Karen Morrison, Giuseppe Lauria, Kelly L. Williams, P. Nigel Leigh, Garth A. Nicholson, Ian P. Blair, Claire S. Leblond, Patrick A. Dion, Guy A. Rouleau, Hardev Pall, Pamela J. Shaw, Martin R. Turner, Kevin Talbot, Franco Taroni, Khrista Boylan, Marka van Blitterswijk, Rosa Rademakers, Jesús Esteban‐Pérez, Alberto García‐Redondo, Wim Robberecht, Adriano Chiò, Cinzia Gellera, Carsten Drepper, Michael Sendtner, Antonia Ratti, Jonathan D. Glass, Jesús S. Mora, Nazlı Başak, Orla Hardiman, Albert C. Ludolph, Peter M. Andersen, Jochen H. Weishaupt, Robert H. Brown, Ammar Al‐Chalabi, Vincenzo Silani, Christopher E. Shaw, Leonard H. van den Berg, Jan H. Veldink, John E. Landers
Bibliographic record
VenueNature Genetics · 2016
Typearticle
Languageen
FieldMedicine
TopicAmyotrophic Lateral Sclerosis Research
Canadian institutionsMcGill UniversityMontreal Neurological Institute and Hospital
FundersNational Institute of Neurological Disorders and StrokeNational Heart, Lung, and Blood InstituteInstituto de Salud Carlos IIINational Health and Medical Research CouncilMedical Research CouncilNational Institutes of HealthDeutsche Gesellschaft für MuskelkrankeNational Human Genome Research InstituteFondazione Italiana di Ricerca per la Sclerosi Laterale AmiotroficaFondation CharcotUniversity of TorontoMinistero della SaluteZonMwCase Western Reserve UniversityBelgian Federal Science Policy OfficeDeutsche ForschungsgemeinschaftBundesministerium für Bildung und ForschungNational Institute on AgingNational Institute for Health and Care ResearchVlaamse regeringIstituto Auxologico ItalianoNational Alzheimer's Coordinating CenterVanderbilt UniversityEU Joint Programme – Neurodegenerative Disease ResearchUniversity of PennsylvaniaMotor Neurone Disease AssociationSouth London and Maudsley NHS Foundation TrustMassachusetts Institute of TechnologyWellcome TrustCanadian Institutes of Health ResearchFonds Wetenschappelijk OnderzoekGerman Network for Motor Neuron DiseasesMuscular Dystrophy AssociationKing's College LondonFundación Española para el Fomento de la Investigación de la Esclerosis Lateral AmiotróficaALS Therapy AllianceE-RareHoward Hughes Medical InstituteUniversity of MiamiBroad Institute
KeywordsAmyotrophic lateral sclerosisBiologyLoss functionGeneticsCandidate geneGeneGenetic associationDiseaseComputational biologyGenotypeSingle-nucleotide polymorphismPhenotypePathologyMedicine
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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.801
Threshold uncertainty score1.000
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 head0.034
GPT teacher head0.309
Teacher spread0.275 · 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; both teacher heads agree on what is shown here.
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
Citations294
Published2016
Admission routes2
Has abstractno