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Record W2603562387 · doi:10.1002/ajmg.a.38125

Normal IQ is possible in Smith‐Lemli‐Opitz syndrome

2017· article· en· W2603562387 on OpenAlexaff
Yasemen Eroğlu, Mina Nguyen‐Driver, Robert D. Steiner, Louise S. Merkens, Mark Merkens, Jean‐Baptiste Roullet, Ellen Roy Elias, Geeta Sarphare, Forbes D. Porter, Chumei Li, Elaine Tierney, Małgorzata J.M. Nowaczyk, Kurt A. Freeman

Bibliographic record

VenueAmerican Journal of Medical Genetics Part A · 2017
Typearticle
Languageen
FieldMedicine
TopicCholesterol and Lipid Metabolism
Canadian institutionsMcMaster University
FundersNational Institute of Child Health and Human DevelopmentEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Center for Complementary and Integrative HealthNational Heart, Lung, and Blood Institute
KeywordsSmith–Lemli–Opitz syndromeMedicineInternal medicineGeneticsEndocrinologyBiology

Abstract

fetched live from OpenAlex

Children with Smith-Lemli-Opitz syndrome (SLOS) are typically reported to have moderate to severe intellectual disability. This study aims to determine whether normal cognitive function is possible in this population and to describe clinical, biochemical and molecular characteristics of children with SLOS and normal intelligent quotient (IQ). The study included children with SLOS who underwent cognitive testing in four centers. All children with at least one IQ composite score above 80 were included in the study. Six girls, three boys with SLOS were found to have normal or low-normal IQ in a cohort of 145 children with SLOS. Major/multiple organ anomalies and low serum cholesterol levels were uncommon. No correlation with IQ and genotype was evident and no specific developmental profile were observed. Thus, normal or low-normal cognitive function is possible in SLOS. Further studies are needed to elucidate factors contributing to normal or low-normal cognitive function in children with SLOS.

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)0.000
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: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.020
GPT teacher head0.323
Teacher spread0.303 · 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

Citations11
Published2017
Admission routes1
Has abstractyes

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Same venueAmerican Journal of Medical Genetics Part ASame topicCholesterol and Lipid MetabolismFrench-language works237,207