MétaCan
Menu
Back to cohort

Pengaruh Oral Motor Excersice terhadap Kesulitan Makan Anak Prasekolah di Kota Ambon

2025· article· en· W4411290794 on OpenAlexaboutno aff
Vernando Yanry Lameky, Grace Jeny Wakanno

Bibliographic record

VenueJOURNAL SCIENTIFIC OF MANDALIKA (JSM) e-ISSN 2745-5955 | p-ISSN 2809-0543 · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicVaried Academic Research Topics
Canadian institutionsnot available
Fundersnot available
KeywordsPsychology

Abstract

fetched live from OpenAlex

Difficulty Eating difficulties in preschool children are challenges that can affect the growth, development, and health of children. One of the main causative factors is oral motor disorders that inhibit the child's ability to chew and swallow food. Oral Motor Exercise (OME) has been proposed as an effective intervention to improve eating skills by stimulating and training oral muscles. This study aims to analyze the effect of OME on eating difficulties in preschool children in Ambon City. The research method used a quasi-experiment with a pre-test and post-test design with a control group involving 30 preschool children divided into intervention and control groups. The intervention group received OME training for four weeks, while the control group only received education about healthy eating patterns. The Montreal Children's Hospital Feeding Scale (MCH-FS) measured eating difficulties before and after the intervention. The results showed that the intervention group experienced significant improvements in eating skills compared to the control group. This suggests that OME effectively improves oral motor coordination and reduces eating difficulties in preschool children. These findings support the integration of OME into pediatric nursing intervention programs and the development of public health policies related to the prevention of eating disorders in children.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0180.003

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 head0.025
GPT teacher head0.288
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
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueJOURNAL SCIENTIFIC OF MANDALIKA (JSM) e-ISSN 2745-5955 | p-ISSN 2809-0543Same topicVaried Academic Research TopicsFrench-language works237,207