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Record W2034737696 · doi:10.1097/dbp.0b013e318146903d

A Case Report of Monozygotic Twins with Smith-Magenis Syndrome

2008· article· en· W2034737696 on OpenAlexaff
Matthew Hicks, Susan A. Ferguson, François P. Bernier, Jean-François Lemay

Bibliographic record

VenueJournal of Developmental & Behavioral Pediatrics · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomic variations and chromosomal abnormalities
Canadian institutionsAlberta Children's HospitalUniversity of Calgary
Fundersnot available
KeywordsMonozygotic twinAutismPsychologyDevelopmental disorderDevelopmental psychologyPhenotypeBehavioral syndromeAutism spectrum disorderZygosityCognitionGeneticsNeuroscienceBiology

Abstract

fetched live from OpenAlex

Monozygotic 3.5-year-old twin boys presented for developmental assessment with a history of global developmental delay, behavioral issues including self-harm, and severe receptive and expressive language delays. Chromosome testing confirmed for both a 17p11.2 interstitial microdeletion commonly seen in Smith-Magenis syndrome (SMS), which is characterized by developmental delay, cognitive impairment, and facial and behavioral phenotype. To our knowledge, this is the first description in the literature of monozygotic twins with SMS. Despite their zygosity, the twins had marked differences in presentation including cardiac and renal anomalies, language development, and behavioral phenotype. Both twins displayed disordered speech development, impairments in social interaction, and stereotyped behaviors consistent with autism spectrum disorder, common in the vast majority of cases of SMS. Examining the differences in behavioral and clinical phenotype in monozygotic twins may lead to a better understanding of the cause of the clinical variability seen in SMS, as well as the natural history of this 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 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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.002
Science and technology studies0.0030.002
Scholarly communication0.0020.002
Open science0.0010.003
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0030.001

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 head0.022
GPT teacher head0.241
Teacher spread0.219 · 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 designCase report
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

Citations18
Published2008
Admission routes1
Has abstractyes

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