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Record W2585327095 · doi:10.1167/17.1.38

Face perception develops similarly across viewpoint in children and adolescents with and without autism spectrum disorder

2017· article· en· W2585327095 on OpenAlexafffund
Jacalyn Guy, Claudine Habak, Hugh R. Wilson, Laurent Mottron, Armando Bertone

Bibliographic record

VenueJournal of Vision · 2017
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsUniversité de MontréalHôpital Rivière-des-PrairiesYork UniversityMcGill University
FundersFonds de Recherche du Québec - Santé
KeywordsPsychologyPerceptionAutism spectrum disorderFace (sociological concept)AutismFace perceptionDevelopmental psychologyIdentity (music)Cognitive psychology

Abstract

fetched live from OpenAlex

Atypical face perception has been associated with the socio-communicative difficulties that characterize autism spectrum disorder (ASD). Growing evidence, however, suggests that a widespread impairment in face perception is not as common as once thought. One important issue arising with the interpretation of this literature is the relationship between face processing and a more general perceptual tendency to focus on local rather than global information. Previous work has demonstrated that when discriminating faces presented from the same view, older adolescents and adults with ASD perform similarly to typically developing individuals. When faces are presented from different views, however, they perform more poorly-specifically, when access to local cues is minimized. In this study, we assessed the cross-sectional development of face identity discrimination across viewpoint using same- and different-view conditions in children and adolescents with and without ASD. Contrary to the findings in adults, our results revealed that all participants experienced greater difficulty identifying faces from different views than from same views, and demonstrated similar age-expected improvements in performance across tasks. These results suggest that differences in face discrimination across views may only emerge beyond the age of 15 years in ASD.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.494

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.017
GPT teacher head0.332
Teacher spread0.315 · 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

Citations6
Published2017
Admission routes2
Has abstractyes

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