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Record W3019795398 · doi:10.1002/ajmg.a.61603

Further delineation of <scp>Basel‐Vanagaite‐Smirin‐Yosef</scp> syndrome: Report of three patients

2020· article· en· W3019795398 on OpenAlexaff
Devon Haynes, Lynda Pollack, Chitra Prasad, Sharan Goobie, Samantha Colaiacovo, Tara Wolfinger, Yves Lacassie

Bibliographic record

VenueAmerican Journal of Medical Genetics Part A · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBiochemical and Molecular Research
Canadian institutionsWestern UniversityLondon Health Sciences Centre
Fundersnot available
KeywordsIntellectual disabilityMicrocephalyMedicinePediatricsEpilepsyFailure to thriveFacial dysmorphismFragile X syndromeSuspectPhenotypeGeneticsGenePsychiatryPsychologyBiology

Abstract

fetched live from OpenAlex

Basel-Vanagaite-Smirin-Yosef syndrome is a recently described autosomal recessive intellectual disability syndrome caused by variants in the MED25 gene. While it was originally identified in Brazil, it was further described in Israel by authors who are now the namesake of the condition. A 2018 publication further contributed to its delineation, but the patient's phenotype was complicated by a dual diagnosis. More recently, an article describing a set of affected siblings was published. We describe three, previously unreported, patients showing clinical variability for this newly defined syndrome. The major features determined by "reverse phenotyping" include significant to profound developmental delays/intellectual disability with absent or delayed speech, epilepsy, ocular abnormalities, cleft lip and/or palate, congenital heart disease, urogenital anomalies, skeletal abnormalities, brain malformations and/or microcephaly, failure to thrive, and dysmorphic features. The authors suggest the delineation of an acronym using the gene name and common features seen across the majority of patients reported so far. This new nomination, MED-DOCS, may help clinicians to recognize, suspect, and remember this novel syndrome.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.190
Threshold uncertainty score0.523

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
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 head0.015
GPT teacher head0.279
Teacher spread0.263 · 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 designBench or experimental
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

Citations9
Published2020
Admission routes1
Has abstractyes

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