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Record W2033864193 · doi:10.1352/1944-7558-118.4.262

Social Behavior and Characteristics of Autism Spectrum Disorder in Angelman, Cornelia de Lange, and Cri du Chat Syndromes

2013· article· en· W2033864193 on OpenAlexaff
Joanna Moss, Patricia Howlin, Richard P. Hastings, Sarah Beaumont, Gemma M. Griffith, Jane Petty, Penny Tunnicliffe, Rachel Yates, Darrelle Villa, Chris Oliver

Bibliographic record

VenueAmerican Journal on Intellectual and Developmental Disabilities · 2013
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsChild, Adolescent and Family Mental Health
Fundersnot available
KeywordsCornelia de Lange SyndromeAngelman syndromeAutismAutism spectrum disorderPsychologySocial communicationDevelopmental psychologySocial relationClinical psychologyPediatricsMedicineSocial psychologyBiologyGenetics

Abstract

fetched live from OpenAlex

We evaluated autism spectrum disorder (ASD) characteristics and social behavior in Angelman (AS; n = 19; mean age = 10.35 years), Cornelia de Lange (CdLS; n = 15; mean age = 12.40 years), and Cri du Chat (CdCS, also known as 5 p-syndrome; n = 19; mean age = 8.80 years) syndromes. The proportion of individuals meeting the ASD cutoff on the Social Communication Questionnaire was significantly higher in the AS and CdLS groups than in the CdCS group (p < .01). The groups demonstrated divergent social behavior profiles during social conditions in which adult availability, adult familiarity, and social demand were manipulated. Social enjoyment was significantly heightened in AS, whereas social approaches were heightened in individuals with CdCS. Social motivation, social communication, and enjoyment were significantly lower in CdLS. The findings highlight the importance of detailed observation when evaluating ASD and social behavior in genetic syndromes.

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)0.002
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 score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.027
GPT teacher head0.275
Teacher spread0.248 · 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

Citations47
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueAmerican Journal on Intellectual and Developmental DisabilitiesSame topicAutism Spectrum Disorder ResearchFrench-language works237,207