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Record W2531771252 · doi:10.1016/j.ajhg.2016.08.023

Association Study of Exon Variants in the NF-κB and TGFβ Pathways Identifies CD40 as a Modifier of Duchenne Muscular Dystrophy

2016· article· en· W2531771252 on OpenAlexaff
Luca Bello, Kevin M. Flanigan, Robert B. Weiss, Diane M. Dunn, Kathryn J. Swoboda, Eduard Gappmaier, Michael Howard, Jacinda B. Sampson, Mark B. Bromberg, Russell J. Butterfield, Lynne M. Kerr, Julaine Florence, Anne M. Connolly, Glenn Lopate, Paul T. Golumbek, Jeanine Schierbecker, Betsy Malkus, Renee Renna, Catherine Siener, Richard S. Finkel, Carsten G. Bönnemann, Līvija Medne, Allan M. Glanzman, Jean Flickinger, Jerry R. Mendell, Wendy King, Linda Lowes, Lindsay N. Alfano, Katherine D. Mathews, Carrie Stephan, Karla S. Laubenthal, Kris Baldwin, Brenda Wong, P. Morehart, Amy Meyer, Cameron E. Naughton, Marcia K. Margolis, Pietro Spitali, Annemieke Aartsma‐Rus, Francesco Muntoni, Irina Zaharieva, Alessandra Ferlini, Eugenio Mercuri, Sylvie Tuffery‐Giraud, Mireille Claustres, Volker Straub, Hanns Lochmüller, Andrea Barp, Sara Vianello, Elena Pegoraro, Jaya Punetha, Heather Gordish‐Dressman, Mamta Giri, Craig M. McDonald, Eric P. Hoffman, Avital Cnaan, Richard T. Abresch, Erik Henricson, Lauren P. Morgenroth, Tina Duong, Vinothini Chidambaranathan, W. Douglas Biggar, Laura McAdam, Jean K. Mah, M. Tulinius, Robert T. Leshner, Carolina Tesi Rocha, Mathula Thangarajh, Andrew J. Kornberg, Monique M. Ryan, Yoram Nevo, Alberto Dubrovsky, Paula R. Clemens, Hoda Abdel‐Hamid, Alan Pestronk, Jean Teasley, Tulio E. Bertorini, Kathryn North, Richard Webster, Hanna Kolski, Nancy L. Kuntz, Sherilyn W. Driscoll, Jose Carlo, Ksenija Gorni, Timothy Lotze, Peter Karachunski, John B. Bodensteiner

Bibliographic record

VenueThe American Journal of Human Genetics · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle Physiology and Disorders
Canadian institutionsStollery Children's Hospital
FundersNational Institute on Disability and Rehabilitation ResearchNational Institute of Arthritis and Musculoskeletal and Skin DiseasesMedical Research CouncilUniversità degli Studi di PadovaU.S. Department of DefenseU.S. Department of EnergyEuropean CommissionChildren's National HospitalNewcastle UniversityNational Institute of Neurological Disorders and StrokeNational Institute for Health and Care ResearchFondazione TelethonMinistero dell’Istruzione, dell’Università e della RicercaUniversity College LondonGreat Ormond Street Hospital for ChildrenU.S. Department of EducationNational Institutes of HealthNIHR Biomedical Research Centre, Royal Marsden NHS Foundation Trust/Institute of Cancer ResearchDuchenne Parent ProjectAssociation Française contre les Myopathies
KeywordsSingle-nucleotide polymorphismGeneticsBiologyDuchenne muscular dystrophyMinor allele frequencyAllelePopulationGeneMedicineGenotype

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.012
GPT teacher head0.255
Teacher spread0.244 · 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

Citations74
Published2016
Admission routes1
Has abstractno

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