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Record W7163344800 · doi:10.35508/eceds.v3i2.9237

Early Childhood Physical Motor Development

2022· article· W7163344800 on OpenAlexaff
Al Ihzan Tajuddin, Ronald Dwi Ardian Fufu, Salmon Runesi

Bibliographic record

VenueEarly Childhood Education Development and Studies (ECEDS) · 2022
Typearticle
Language
FieldSocial Sciences
TopicChild Development and Education
Canadian institutionsSelkirk College
Fundersnot available
KeywordsMotor skillChild developmentVariety (cybernetics)Early childhoodPhysical developmentMaturity (psychological)Motor system

Abstract

fetched live from OpenAlex

Motor development is one aspect that must be considered in its development in early childhood. Motor development is often used as a benchmark to prove that children are growing and developing well. Motor development is something that talks about coordinated physical movements, so that in its development it takes a variety of appropriate stimulation for early childhood. Motor development is one of the most important factors in the development of the individual as a whole. Basically, this development develops in line with the maturity of the nerves and muscles of the child. Thus, every movement, no matter how simple, is the result of a complex interaction pattern of various parts of the system in the body that is controlled by the brain. The results of this study indicate that children who have good physical-motor development, when children are able to coordinate their body muscle movements optimally. Conducive environment, parenting patterns, nutritious food are factors that support children's physical-motor development, especially when they are still under the age of five (toddlers).

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 score0.024
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0170.002

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 head0.020
GPT teacher head0.283
Teacher spread0.263 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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