MétaCan
Menu
Back to cohort
Record W4412563111 · doi:10.1212/wnl.0000000000213868

Development and Adaptive Function in Individuals With <i>SCN2A</i> -Related Disorders

2025· article· en· W4412563111 on OpenAlexaff
Beatrice S. Goad, Jill Rodda, Daniel Bamborschke, Isabella Overmars, Rachel Kerr, Ittai Bushlin, S. Chopra, Rohini Coorg, Gabriel Dabscheck, Jeremy L. Freeman, Mark T. Mackay, Orrin Devinsky, Renzo Guerrini, Elena Parrini, Bigna K. Bölsterli, Inna Hughes, Linda Huh, Mahesh Kamate, A. Barry Kunz, Gia Melikishvili, Christina Miteff, Kenneth A. Myers, Heather E. Olson, Annapurna Poduri, Sekhar Pillai, Catherine J. Riney, Adriane Sinclair, Sophie Calvert, Thomas Q. Reynolds, Ana Roche Martínez, Angelo Russo, Lynette G. Sadleir, Icíar Sánchez‐Albisua, Stefano Sartori, Stephanie A. Shea, Constance Smith‐Hicks, Claire G. Spooner, Rhys H. Thomas, Simone Ardern‐Holmes, Richard Webster, Massimiliano Valeriani, Pierangelo Veggiotti, Silvia Masnada, Tyson L. Ware, Michael Yoong, Géza Berecki, Angela De Dominicis, Nicola Specchio, Marina Trivisano, Rikke S. Møller, Markus Wolff, Walid Fazeli, Ingrid E. Scheffer, Katherine B. Howell

Bibliographic record

VenueNeurology · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomic variations and chromosomal abnormalities
Canadian institutionsMcGill University Health CentreMontreal Children's HospitalBC Children's Hospital
Fundersnot available
KeywordsFunction (biology)MedicineBiologyGenetics

Abstract

fetched live from OpenAlex

BACKGROUND AND OBJECTIVES: -related disorders, although descriptions are limited. We aimed to determine trajectories and outcomes of development and adaptive function. METHODS: -containing 2q24.3 copy number variants (CNVs) were considered separately. We collected medical and developmental history from parents/caregivers and medical records. Adaptive function and behavior were characterized using functional classification system levels and Vineland Adaptive Behavior Scales-3 (VABS-3) Parent/Caregiver Form. We repeated analyses on individuals with variants known to result in gain-of-function (GOF, typically EO phenotypes) or loss-of-function (LOF, typically LO phenotypes). RESULTS: < 0.01). Analyses of individuals with confirmed GOF/LOF variants (n = 57) showed similar results to the EO/LO analyses. DISCUSSION: -related disorders is extremely broad. Phenotypic subgroups provide prognostic information and critically inform clinical trial design.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

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)0.001
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 score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.004
GPT teacher head0.182
Teacher spread0.178 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueNeurologySame topicGenomic variations and chromosomal abnormalitiesFrench-language works237,207