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Record W2800370121 · doi:10.3389/fpsyg.2018.00847

Analogical Reasoning in Children With Autism Spectrum Disorder: Evidence From an Eye-Tracking Approach

2018· article· en· W2800370121 on OpenAlexaff
Enda Tan, Xueyuan Wu, Tracy K. Nishida, Dan Huang, Zhe Chen, Li Yi

Bibliographic record

VenueFrontiers in Psychology · 2018
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsUniversity of British Columbia
FundersNational Office for Philosophy and Social SciencesNational Natural Science Foundation of China
KeywordsPsychologyAutismAutism spectrum disorderEye trackingCognitionEye movementTypically developingAnalogical reasoningCognitive psychologyDevelopmental psychologyGazeExecutive functionsNeuroscience

Abstract

fetched live from OpenAlex

The present study examined analogical reasoning in children with autism spectrum disorder (ASD) and its relationship with cognitive and executive functioning and processing strategies. Our findings showed that although children with ASD were less competent in solving analogical problems than typically developing children, this inferior performance was attributable to general cognitive impairments. Eye-movement analyses revealed that children with ASD paid less attention to relational items and showed fewer gaze shifts between relational locations. Nevertheless, these eye-movement patterns did not predict autistic children’s behavioral performance. Together, our findings suggest that ASD per se does not entail impairments in analogical reasoning. The inferior performance of autistic children on analogical reasoning tasks is attributable to deficits in general cognitive and executive functioning.

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)0.005
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 score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
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 head0.032
GPT teacher head0.351
Teacher spread0.319 · 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

Citations8
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueFrontiers in Psychology→Same topicAutism Spectrum Disorder Research→French-language works237,207→