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Record W4312872914 · doi:10.57251/sin.v2i1.211

Analisis Bahasa Anak pada Usia 2 Tahun dari Aspek Fonologi, Morfologi, Sintaksis, dan Semantik

2022· article· en· W4312872914 on OpenAlexaff
Zira Fatmaira

Bibliographic record

VenueSintaks Jurnal Bahasa & Sastra Indonesia · 2022
Typearticle
Languageen
FieldComputer Science
TopicEducational Methods and Media Use
Canadian institutionsKootenay Association for Science & Technology
Fundersnot available
KeywordsVocabularySyntaxPhonologyLinguisticsLanguage acquisitionFirst languageSemantics (computer science)Spoken languagePsychologyHeritage languageComputer science

Abstract

fetched live from OpenAlex

Mother tongue is the first language mastered by humans since the beginning of their life through interaction with fellow members of the language community, such as family and the environmental community. This shows that the first language is an initial process obtained by children in recognizing sounds and symbols called language. The process of language acquisition also develops with increasing age of children, from months of age to years of age, but what is discussed in this study is the age of 2 years 6 months in which the language process has begun to be clearly seen in the vocabulary spoken by the child. This study aims to determine the language acquisition of children aged 2 years 6 months at the level of phonology, morphology, syntax and semantics. This research is expected to be one of the information materials in terms of research on language acquisition. The research method used in this research is a qualitative method with a case study approach. Through this qualitative method, the fathian phonetic system will be described at the age of 2 years and 6 months.

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)0.002
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 score0.016
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.023
GPT teacher head0.276
Teacher spread0.253 · 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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