MétaCan
Menu
Back to cohort
Record W4393386186 · doi:10.1016/j.ajhg.2024.03.008

Exome copy number variant detection, analysis, and classification in a large cohort of families with undiagnosed rare genetic disease

2024· article· en· W4393386186 on OpenAlexfundno aff
Gabrielle Lemire, Alba Sanchis‐Juan, Kathryn Russell, Samantha Baxter, Katherine R. Chao, Moriel Singer‐Berk, Emily Groopman, Isaac Wong, Eleina England, Julia K. Goodrich, Lynn Pais, Christina Austin‐Tse, Stephanie DiTroia, Emily O’Heir, Vijay Ganesh, Monica H. Wojcik, Emily Evangelista, Hana Snow, Ikeoluwa Osei‐Owusu, Jack Fu, Mugdha Singh, Yulia Mostovoy, Steve S. Huang, Kiran Garimella, Samantha L. Kirkham, Jennifer E. Neil, Diane D. Shao, Christopher A. Walsh, Emanuela Argilli, Carolyn Le, Elliott H. Sherr, Joseph G. Gleeson, Shirlee Shril, Ronen Schneider, Friedhelm Hildebrandt, Vijay G. Sankaran, Jill A. Madden, Casie A. Genetti, Alan H. Beggs, Pankaj B. Agrawal, Kinga M. Bujakowska, Emily Place, Eric A. Pierce, Sandra Donkervoort, Carsten G. Bönnemann, Lyndon Gallacher, Zornitza Stark, Tiong Yang Tan, Susan M. White, Ana Töpf, Volker Straub, Mark D. Fleming, Martin R. Pollak, Katrin Õunap, Sander Pajusalu, Kirsten A. Donald, Zandrè Bruwer, Gianina Ravenscroft, Nigel G. Laing, Daniel G. MacArthur, Heidi L. Rehm, Michael E. Talkowski, Harrison Brand, Anne O’Donnell‐Luria

Bibliographic record

VenueThe American Journal of Human Genetics · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomic variations and chromosomal abnormalities
Canadian institutionsnot available
FundersH2020 European Research CouncilEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute of Neurological Disorders and StrokeEstonian Research Competency CouncilLGMD2D FoundationNational Institute of Mental HealthSanofi GenzymeNational Institute of Dental and Craniofacial ResearchUC Berkeley College of ChemistryNational Health and Medical Research CouncilMuscular Dystrophy UKState Government of VictoriaKurt+Peter FoundationUniversity of California, San DiegoMurdoch Children's Research InstituteFonds de Recherche du Québec - SantéLimb Girdle Muscular Dystrophy 2IMassachusetts General HospitalChildren’s Hospital of Wisconsin Research InstituteEuropean CommissionNational Institute of Child Health and Human DevelopmentNational Institute of Diabetes and Digestive and Kidney DiseasesSanofiResearch to Prevent BlindnessNational Institutes of HealthTürkiye Bilimsel ve Teknolojik Araştırma KurumuFoundation Fighting BlindnessLimb Girdle Muscular Dystrophy 2i Research FundNational Human Genome Research InstituteUltragenyx PharmaceuticalNational Eye InstituteEesti TeadusagentuurAutism Speaks
KeywordsCopy-number variationExome sequencingExomeGeneticsGenomicsBiologyGenetic testingMendelian inheritanceMedical geneticsComputational biologyPhenotypeGenomeGene

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)0.003
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 score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.005
GPT teacher head0.240
Teacher spread0.234 · 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

Citations21
Published2024
Admission routes1
Has abstractno

Explore more

Same venueThe American Journal of Human GeneticsSame topicGenomic variations and chromosomal abnormalitiesFrench-language works237,207