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Record W4404070612 · doi:10.46827/ejse.v10i7.5639

FACTORS INFLUENCING THE SOCIAL-EMOTIONAL BEHAVIOR OF CHILDREN WITH AUTISM: THE INFLUENCE OF PSYCHOMOTOR CLUMSINESS

2024· article· en· W4404070612 on OpenAlexaff
Sarris Dimitrios, Tsodoulos Kiriakos, K. Antonios Travlos, Vassiliki Siafaka, Emmanouil Skordilis, Christopoulou Foteini, Panagoula Papadimitropoulou, Tryfon Mavropalias, Eleni Thanou

Bibliographic record

VenueEuropean Journal of Special Education Research · 2024
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsEducation and Early Childhood Development
Fundersnot available
KeywordsPsychomotor learningAutismPsychologyPsychomotor retardationDevelopmental psychologySocial emotional learningClinical psychologyMedicinePsychiatryCognition

Abstract

fetched live from OpenAlex

Children with autism manifest detection first, then parallel behavior, cooperation, autistic behavior, and communicate less with other children. Higher autism functioning was associated with probing, parallel, cooperative and partnering behavior and lower with autistic behavior. Children had more difficulty in tests where the children were stationary and the environment was changing, followed by tests where the children were moving, and better performance was observed in tests where the children were stationary, and the environment was stable. Psychomotor clumsiness produced negative effects on socio-emotional behavior, while physical activity within school and group play produced positive effects. Autism functionality emerged as a moderator in the relationship between psychomotor clumsiness and socioemotional behavior. Article visualizations:

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)0.004
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 score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
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 head0.070
GPT teacher head0.391
Teacher spread0.321 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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