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Record W2015640442 · doi:10.1155/2011/657383

Eye Movement Sequences during Simple versus Complex Information Processing of Scenes in Autism Spectrum Disorder

2011· article· en· W2015640442 on OpenAlexaff
Sheena K. Au‐Yeung, Valerie Benson, Monica S. Castelhano, Keith Rayner

Bibliographic record

VenueAutism Research and Treatment · 2011
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsQueen's University
FundersWorldwide Universities Network
KeywordsAutism spectrum disorderEye movementTask (project management)PerceptionCognitive psychologyPsychologyAutismMovement (music)Simple (philosophy)Information processingComputer scienceArtificial intelligenceDevelopmental psychologyNeuroscience

Abstract

fetched live from OpenAlex

Minshew and Goldstein (1998) postulated that autism spectrum disorder (ASD) is a disorder of complex information processing. The current study was designed to investigate this hypothesis. Participants with and without ASD completed two scene perception tasks: a simple "spot the difference" task, where they had to say which one of a pair of pictures had a detail missing, and a complex "which one's weird" task, where they had to decide which one of a pair of pictures looks "weird". Participants with ASD did not differ from TD participants in their ability to accurately identify the target picture in both tasks. However, analysis of the eye movement sequences showed that participants with ASD viewed scenes differently from normal controls exclusively for the complex task. This difference in eye movement patterns, and the method used to examine different patterns, adds to the knowledge base regarding eye movements and ASD. Our results are in accordance with Minshew and Goldstein's theory that complex, but not simple, information processing is impaired 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)0.000
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 score0.566
Threshold uncertainty score0.743

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.138
GPT teacher head0.368
Teacher spread0.230 · 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

Citations17
Published2011
Admission routes1
Has abstractyes

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