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Record W2080912082 · doi:10.1080/17518420701688607

The performance profile on the Wisconsin Card Sorting Test of a group of children with cerebral palsy aged between 9 and 12

2008· article· en· W2080912082 on OpenAlexaff
Line Nadeau, Marie-Egrave ve Routhier, Réjean Tessier

Bibliographic record

VenueDevelopmental Neurorehabilitation · 2008
Typearticle
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsHôpital Saint-François d'AssiseUniversité LavalCentre for Interdisciplinary Research in Rehabilitation
Fundersnot available
KeywordsCerebral palsyWisconsin Card Sorting TestTest (biology)Physical medicine and rehabilitationPsychologyMedicinePhysical therapyAudiologyGerontologyCognitionPsychiatryNeuropsychology

Abstract

fetched live from OpenAlex

PURPOSE: The aim of this study was to determine the performance profile of a group of children with cerebral palsy (CP) on the Wisconsin Card Sorting Test (WCST). METHODS: The sample consisted of 102 children aged between 9-12, divided into two groups: the clinical group consisted of 52 children with in mainstream class (37 with hemiplegia and 15 with diplegia), while the comparison group comprised 50 children matched for class, gender, age and socioeconomic status. RESULTS: The findings showed that children with CP make more non-perseverative errors, they completed fewer categories, required more trials to complete the first category and gave fewer conceptual responses than control children. Children with diplegia are distinguished more from comparison children than children with hemiplegia. CONCLUSION: The results suggest a difficulty in initial conceptualization that could be attributable to a slow rate of information processing. Delayed maturation of the nervous system is likely to be implied.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.261

Codex and Gemma teacher scores by category

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

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 head0.016
GPT teacher head0.221
Teacher spread0.206 · 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.

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

Citations20
Published2008
Admission routes1
Has abstractyes

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