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Record W2984908309 · doi:10.1080/17518423.2019.1687598

Systematic Review of the Main Motor Scales for Clinical Assessment of Individuals with down Syndrome

2019· review· en· W2984908309 on OpenAlexaboutno aff
Cristina Hamamura Moriyama, Thaís Massetti, Tânia Brusque Crocetta, Talita Dias da Silva, Zan Mustacchi, Regiani Guarnieri, Luíz Carlos de Abreu, Amanda Vitória Lacerda de Araújo, Lilian Del Ciello de Menezes, Carlos Bandeira de Mello Monteiro, Cláudio Leone

Bibliographic record

VenueDevelopmental Neurorehabilitation · 2019
Typereview
Languageen
FieldMedicine
TopicInfant Development and Preterm Care
Canadian institutionsnot available
Fundersnot available
KeywordsMovement assessmentGross motor skillObservational studyPhysical medicine and rehabilitationPsychologyBayley Scales of Infant DevelopmentMotor skillPhysical therapyMedicineDevelopmental psychologyCognitionPsychiatryPsychomotor learning

Abstract

fetched live from OpenAlex

Objective: The aim of the present review was to identify the motor scales currently used to assess individuals with Down Syndrome (DS).Method: PubMed, WOS and BVS databases were systematically searched to identify the most relevant published studies that used motor scales in the evaluation of individuals with DS.Results: Of the 99 studies that met the eligibility criteria in this process, 20 experimental and observational studies were found to fully meet the eligibility criteria.Conclusion: We identified several motor scales including the Alberta Infant Motor Scale (AIMS), Test of Infant Motor Performance (TIMP), BAYLEY, Peabody Gross Motor Scale (PGMS-PDMS-GM), Gross Motor Function Measure (GMFM), Movement Assessment Battery for Children (MABC) and Pediatric Evaluation of Disability Inventory (PEDI).

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.032
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.001
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 head0.052
GPT teacher head0.392
Teacher spread0.340 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations18
Published2019
Admission routes1
Has abstractyes

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