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Record W2133118876 · doi:10.1177/1362361309348943

Mealtime problems in children with Autism Spectrum Disorder and their typically developing siblings: A comparison study

2010· article· en· W2133118876 on OpenAlexaff
Geneviève Nadon, Debbie Ehrmann Feldman, Winnie Dunn, Erika G. Gisel

Bibliographic record

VenueAutism · 2010
Typearticle
Languageen
FieldMedicine
TopicChild Nutrition and Feeding Issues
Canadian institutionsMcGill UniversityUniversité de Montréal
Fundersnot available
KeywordsAutism spectrum disorderPsychologySiblingAutismTypically developingDevelopmental psychologyClinical psychology

Abstract

fetched live from OpenAlex

Many children with autism spectrum disorders (ASD) have mealtime problems. Diagnosis and the social environment may influence eating behaviours. We examined whether children with ASD have more mealtime problems than their typically developing siblings, and whether age and sex are associated with mealtime problems. Forty-eight families participated in this cross sectional study by completing a questionnaire (Eating Profile) for their child with ASD, 3 to 12 years of age. A second Eating Profile was completed for the sibling nearest in age without ASD. Children with ASD had a mean of 13.3 eating problems, with lack of food variety predominating. Siblings had 5.0 problems. Children with ASD had more eating problems as infants. Older children tended to have fewer problems than younger children. This study points to the importance of screening for mealtime problems. Children with ASD had significantly more mealtime problems than their sibling living in the same social environment.

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)0.002
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 score0.022
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0010.000
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 head0.014
GPT teacher head0.269
Teacher spread0.255 · 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

Citations186
Published2010
Admission routes1
Has abstractyes

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