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Record W4404727330 · doi:10.1016/j.xhgg.2024.100387

MGA-related syndrome: A proposed novel disorder

2024· article· en· W4404727330 on OpenAlexaff
Bobbi McGivern, Michelle Morrow, Erin Torti, Kirsty McWalter, Ingrid M. Wentzensen, Kristin G. Monaghan, Amanda Gerard, Laurie Robak, David Chitayat, Claire Botsford, Sarah Jurgensmeyer, Peter Leahy, Paul Kruszka

Bibliographic record

VenueHuman Genetics and Genomics Advances · 2024
Typearticle
Languageen
FieldMedicine
TopicNeurofibromatosis and Schwannoma Cases
Canadian institutionsUniversity of TorontoMount Sinai Hospital
Fundersnot available
KeywordsComputer scienceMedicinePsychology

Abstract

fetched live from OpenAlex

MGA (OMIM: 616061) encodes a dual-specificity transcription factor that regulates the expression of Max-network and T-box family target genes, important in embryogenesis. Previous studies have linked MGA to various phenotypes, including neurodevelopmental disorders, congenital heart disease, and early-onset Parkinson's disease. Here, we describe the clinical phenotype of individuals with de novo, heterozygous predicted loss-of-function variants in MGA, suggesting a unique disorder involving both neurodevelopmental and congenital anomalies. In addition to developmental delays, certain congenital anomalies were present in all individuals in this cohort including cardiac anomalies, male genital malformations, and craniofacial dysmorphisms. Additional findings seen in multiple individuals in this cohort include hypotonia, abnormal brain imaging, hearing loss, sleep dysfunction, urinary issues, skeletal abnormalities, and feeding difficulties. These findings provide support for MGA as a gene intolerant to protein truncation with a broad phenotypic spectrum.

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 distilled prediction

Teacher imitation

Not 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.866
Threshold uncertainty score0.581

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.014
GPT teacher head0.271
Teacher spread0.256 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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
Published2024
Admission routes1
Has abstractyes

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