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Association between motor development of typical children and head and trunk alignment

2016· article· en· W2567111031 on OpenAlexaboutno aff
Micheli Martinello, Maria W. Louzada, Tamiris Beppler Martins, Aline Dandara Rafael, Gilmar Moraes Santos

Bibliographic record

VenueManual Therapy Posturology & Rehabilitation Journal · 2016
Typearticle
Languageen
FieldMedicine
TopicInfant Development and Preterm Care
Canadian institutionsnot available
Fundersnot available
KeywordsTrunkKinematicsElbowPhysical medicine and rehabilitationUpper trunkElbow flexionAssociation (psychology)Motor controlMedicinePsychologyAnatomyPhysicsBiology

Abstract

fetched live from OpenAlex

Introduction: Among the typical motor development, it is considered the neck control as being of great importance. Although there is no consensus of the best positioning for stimulation of neck control, it is clear in the literature the positive association between the prone position and the typical motor development according to the age of infants. Objective: To investigate the association between the kinematic variables related to neck control and bracing with age and motor performance in the prone position of typical children. Methods: 30 children participated in the study. Motor development was assessed by Alberta Infant Motor Scale (AIMS), and the alignment of the head, trunk and upper limb was analyzed through kinematic analysis in the prone position. Results: with the association of the variables: age, AIMS in the prone position and the kinematic variables (inclination of the head, trunk extension, shoulder angle and elbow angle), was observed that the increase in age and the best performance in the prone position corresponding to the inclination of the head. The trunk and elbow extension also increases. Conclusion: there was a positive association between the variables age and motor performance in the prone position of typical children, with kinematics variables the inclination of the head, the trunk and the elbow extension.

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)0.001
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 score0.079
Threshold uncertainty score0.319

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.010
GPT teacher head0.276
Teacher spread0.266 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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