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Record W2048154027 · doi:10.3104/reports.298

Gross motor skill acquisition in adolescents with Down syndrome

2006· article· en· W2048154027 on OpenAlexafffund
Sarah Meegan, Brian K. V. Maraj, Daniel J. Weeks, Romeo Chua

Bibliographic record

VenueDown Syndrome Research and Practice · 2006
Typearticle
Languageen
FieldPsychology
TopicChildren's Physical and Motor Development
Canadian institutionsUniversity of British ColumbiaSimon Fraser UniversityUniversity of Alberta
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPsychologyGross motor skillMotor skillNonverbal communicationMultiple baseline designAudiologyDevelopmental psychologyMedicine

Abstract

fetched live from OpenAlex

The purpose of this study was to assess whether verbal-motor performances deficits exhibited by individuals with Down syndrome limited their ability to acquire gross motor skills when given visual and verbal instruction together and then transferred to either a visual or verbal instructional mode to reproduce the movement. Nine individuals with Down syndrome (6 males, 3 females) performed 3 gross motor skills. Both visual and verbal instructional guidance was given to the participants over a 4-day period. Twenty-four hours later, the participants were video recorded as they produced the movements (used as baseline measures). On Day 6, they were randomly assigned into verbal and visual groups and required to reproduce the skills while the experimenter provided either visual demonstration or verbal instructions depending on the group. Based on skill performance scores, participants in the verbal-motor performance group demonstrated a lower level of proficiency and an increased number of performance errors when compared to participants in the visual-motor performance group. Moreover, while the visual group demonstrated an increase in performance levels compared to baseline measures, the opposite effect was seen for the verbal group.

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)0.002
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 score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
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)0.0010.000

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 head0.027
GPT teacher head0.347
Teacher spread0.320 · 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

Citations31
Published2006
Admission routes2
Has abstractyes

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