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Record W2263966921 · doi:10.7939/r3mk6k

A comparison of two computer-based programs designed to improve facial expression understanding in children with autism

2011· article· en· W2263966921 on OpenAlexaff
Andrew Sung

Bibliographic record

VenueUniversity of Alberta Library · 2011
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsAutismFacial expressionExpression (computer science)Computer sciencePsychologyArtificial intelligenceHuman–computer interactionDevelopmental psychologyProgramming language

Abstract

fetched live from OpenAlex

This randomized clinical trial compared models used to explain facial expression understanding difficulties experienced by individuals with autism. The intervention effects of two computer-based training programs, The Transporters and Let’s Face It! were investigated in young children with autism (N = 21), aged 4-8 years old. The Transporters is an animated series designed to enhance emotion comprehension informed by Theory of Mind and Extreme Male Brain theories. Let’s Face It! has seven interactive games designed to improve children’s visual face perception strategies and is informed by Weak Central Coherence theory. Children were assessed on measures before and after 20 hours of intervention. Compared to children randomized to a no treatment control group (n = 7), children receiving The Transporters training (n = 8) or Let’s Face It! program (n = 6) experienced no significant improvement. Verbal ability and age of participants was linked to performance on the facial understanding measures.

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 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 score0.680
Threshold uncertainty score0.532

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.049
GPT teacher head0.256
Teacher spread0.207 · 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 teacher head, 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

Citations2
Published2011
Admission routes1
Has abstractyes

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