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Record W201960062 · doi:10.1123/apaq.30.3.213

Nature of Spatial Coupling in Children With and Without Developmental Coordination Disorder in Ball Catching

2013· article· en· W201960062 on OpenAlexaff
Eryk Przysucha, Brian K. V. Maraj

Bibliographic record

VenueAdapted Physical Activity Quarterly · 2013
Typearticle
Languageen
FieldPsychology
TopicChildren's Physical and Motor Development
Canadian institutionsUniversity of AlbertaLakehead University
Fundersnot available
KeywordsPsychologyDevelopmental psychologyMotor coordinationContext (archaeology)Typically developingPhysical medicine and rehabilitationMedicineNeuroscienceBiology

Abstract

fetched live from OpenAlex

The nature of intra- and interlimb (bimanual) coordination was examined in ten boys with (M = 10.5 years, SD = 1.0) and without DCD (M = 10.8 years, SD = .9) in a two-handed catching task. Children with developmental coordination disorder (DCD) caught significantly fewer balls (MDCD = 56%, SD = 17.6 vs. MnoDCD = 93%, SD = 7.5), and both groups solved the "degrees of freedom problem" differently at intralimb level of coordination. Typically developing children coupled and decoupled the respective spatial relations, whereas the majority of children with DCD segmented their actions. At interlimb level, both groups exhibited a comparable degree of spatial symmetry. However, individual profiles also showed that children with varying degrees of movement issues exhibited movement patterns that were qualitatively and functionally diverse. Overall, in the context of previous research on interlimb coordination it appears that spatial, in addition to temporal organization, may be jeopardized in at least some children with DCD.

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)0.004
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 score0.017
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.006
GPT teacher head0.243
Teacher spread0.237 · 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

Citations10
Published2013
Admission routes1
Has abstractyes

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