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Record W2105748285 · doi:10.1177/1362361300004004003

How High-Functioning Children with Autism Understand Real and Deceptive Emotion

2000· article· en· W2105748285 on OpenAlex
Maureen Dennis, Linda Lockyer, Anne L. Lazenby

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAutism · 2000
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsHospital for Sick Children
FundersAmerican Academy of Child and Adolescent Psychiatry
KeywordsAutismPsychologyFacial expressionDevelopmental psychologyHigh-functioning autismExpression (computer science)Emotional expressionCognitive psychologyAutism spectrum disorderCommunication

Abstract

fetched live from OpenAlex

Autism is associated with problems in understanding and expressing emotion. We compared the ability of eight high- functioning children with autism (i.e. those with IQ scores ≥ 70) and eight age- and gender-matched controls with similar oral language development, to understand the facial expression of real and deceptive emotion. Children with autism had limited understanding of socially derived emotion. Although they could relate emotions to standard facial expressions, they were less able than controls to indicate the real emotions story characters feel, the deceptive emotions they express in the face, or the social reasons prompting a deceptive facial expression. For high- function children with autism, facial expressions may function as lexical codes but not as forms of social communication that modify beliefs.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.918
Threshold uncertainty score0.752

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.019
GPT teacher head0.243
Teacher spread0.224 · 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