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Facial expression of affect in children with Cornelia de Lange syndrome

2007· article· en· W2105964357 on OpenAlexaff
L. Collis, Joanna Moss, Jagjeet Jutley, Kim Cornish, Chris Oliver

Bibliographic record

VenueJournal of Intellectual Disability Research · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Syndromes and Imprinting
Canadian institutionsMcGill University
Fundersnot available
KeywordsCornelia de Lange SyndromeAffect (linguistics)PsychologyFacial expressionDevelopmental psychologyMedicinePediatricsCommunication

Abstract

fetched live from OpenAlex

BACKGROUND: Individuals with Cornelia de Lange syndrome (CdLS) have been reported to show comparatively high levels of flat and negative affect but there have been no empirical evaluations. In this study, we use an objective measure of facial expression to compare affect in CdLS with that seen in Cri du Chat syndrome (CDC) and a group of individuals with a mixed aetiology of intellectual disabilities (ID). METHOD: Observations of three groups of 14 children with CdLS, CDC and mixed aetiology of ID were undertaken when a one-to-one interaction was ongoing. RESULTS: There was no significant difference between the groups in the duration of positive, negative or flat affect. However, the CdLS group displayed a significantly lower ratio of positive to negative affect than children in the other groups. DISCUSSION: This difference partially confirms anecdotal observations and could be due to the expression of pain caused by health problems associated with CdLS or neurological expression of the CdLS gene in facial muscles related to expression of positive affect. However, further research is needed to directly test these possible associations.

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)0.002
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 score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
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 head0.036
GPT teacher head0.346
Teacher spread0.310 · 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

Citations27
Published2007
Admission routes1
Has abstractyes

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