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Record W4225106855 · doi:10.1007/s10803-022-05570-7

Atypical Tactile Perception in Early Childhood Autism

2022· article· en· W4225106855 on OpenAlexafffund
Svenja Espenhahn, Kate Godfrey, Sakshi Kaur, Carly A. McMorris, Kara Murias, Mark Tommerdahl, Signe Bray, Ashley D. Harris

Bibliographic record

VenueJournal of Autism and Developmental Disorders · 2022
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsHotchkiss Brain InstituteOntario Brain InstituteAlberta Children's HospitalUniversity of Calgary
FundersAlberta Children's Hospital Research InstituteSick Kids FoundationHotchkiss Brain InstituteMathison Centre for Mental Health Research and EducationCanada Foundation for InnovationHotchkiss Brain Institute, University of Calgary
KeywordsNeurotypicalAutismPsychologyPerceptionAudiologyDevelopmental psychologyTactile perceptionCognitive psychologyAutism spectrum disorderNeuroscienceMedicine

Abstract

fetched live from OpenAlex

We assessed different aspects of tactile perception in young children (3-6 years) with autism. Autistic and neurotypical children completed vibrotactile tasks assessing reaction time, amplitude discrimination (sequential and simultaneous) and temporal discrimination (temporal order judgment and duration discrimination). Autistic children had elevated and more variable reaction times, suggesting slower perceptual-motor processing speed and/or greater distractibility. Children with autism also showed higher amplitude discrimination and temporal order judgement thresholds compared to neurotypical children. Tactile perceptual metrics did not associate with social or tactile sensitivities measured by parent-reports. Altered tactile behavioral responses appear in early childhood, can be quantified but appear dissociated from sensitivity. This implies these measures are complementary, but not necessarily related, phenomena of atypical tactile perception in autism.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.539
Threshold uncertainty score1.000

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 science0.0000.000
Research integrity0.0000.001
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 head0.013
GPT teacher head0.252
Teacher spread0.239 · 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.

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

Citations27
Published2022
Admission routes2
Has abstractyes

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