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Record W3119621869 · doi:10.33088/jmk.v7i2.231

PERBEDAAN KELANCARAN PENGELUARAN ASI IBU NIFAS SETELAH PERAWATAN PAYUDARA

2018· article· en· W3119621869 on OpenAlexaff
Atika Asta Octora

Bibliographic record

VenueJURNAL MEDIA KESEHATAN · 2018
Typearticle
Languageen
FieldMedicine
TopicPublic Health and Nutrition
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsBreastfeedingBreast milkMedicinePopulationBreast feedingObstetricsDemographyGynecologyPediatricsEnvironmental healthBiology

Abstract

fetched live from OpenAlex

Breast milk (ASI) is the perfect food for infants and contains all the nutrients necessary for the grow than development of infants, issue in this study is the low coverage of exclusive breast feeding for the city of Bengkulu who have not achieved the national target.The purpose of this study was to determine the effect of the Smooth Implementation of Breast Care Spending on Mother Postpartum breast milk in the Work Area Health Center Sukamerindu 2014. This study used a Quasi-Experimental design using Pre-test and Post test design. The independent variabel was the treatment of breast, while the dependent variabel is the smooth expenditure breast milk. The population was all of 1-7 days postpartum mother. It was 30 people. The sampling technique used is total sampling that (15 treatment group and 15 control group). This study starts from 01 January to12 February 2014 in the Work Area Health Center Sukamerindu. From the research results obtained in the treatment group was average of smoothness ASI output prior to treatment was 4.93 and after breast care is 9.33. In the control group the average of smoothness of spending breastfeeding in the first observation was 4.73 and the second observation is 7.07. Processing data using the t test with α = 0.05 obtained significant value ρ = 0.000 , it means ρ< α or ρ = 0.000 < α = 0.05 means that there is an influence on breast care changes in the smooth of breast milk, from breast milk is not out to be out.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.246
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.028
GPT teacher head0.319
Teacher spread0.291 · 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; both teacher heads agree on what is shown here.

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
Published2018
Admission routes1
Has abstractyes

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