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Record W1987354719 · doi:10.5539/jedp.v5n1p88

Fine Motor Skills Relate to Visual Memory in Autism Spectrum Disorder

2015· article· en· W1987354719 on OpenAlexvenueno aff
Yasuko Funabiki, Tadao Mizutani, Toshiya Murai

Bibliographic record

VenueJournal of Educational and Developmental Psychology · 2015
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsnot available
FundersJapan Society for the Promotion of Science
KeywordsAutism spectrum disorderPsychologyVisual memoryWechsler Adult Intelligence ScaleImpaired memoryAudiologyDevelopmental psychologyAutismPopulationSpectrum disorderCognitionCognitive psychologyNeurosciencePsychiatryMedicine

Abstract

fetched live from OpenAlex

Memory function is an important determinant of behavioral manifestations and social adaptations in individuals with autism spectrum disorder (ASD). While a number of studies have examined memory function in people with ASD, whether impaired memory is characteristic of ASD is unclear. This controversy is likely because of the heterogeneity of the ASD population. However, few studies have investigated the relationship between memory function and the severity of various autistic symptoms. Therefore, to assess such relationships, we used the Wechsler Memory Scale-Revised and the Multi-dimensional Scale for Pervasive developmental disorder and Attention deficit/hyperactivity disorder, which encompasses symptoms comorbid with ASD, to assess 36 individuals with high-functioning ASD. Participants showed average performance in the memory battery. Interestingly, scores reflecting fine motor skills were significantly associated with visual memory performance. That is, individuals with ASD who exhibit impaired fine motor skills showed poor visual memory. This finding implies that memory variability may be associated with developmental trajectory in people with 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 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)0.000
metaresearch head score (Gemma)0.003
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 score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.371
Teacher spread0.339 · 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

Citations4
Published2015
Admission routes1
Has abstractyes

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