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Record W4230392482 · doi:10.32831/jik.v8i1.234

[no title]

2019· article· W4230392482 on OpenAlexaboutno aff
Wiwit Dwi Nurbadriyah

Bibliographic record

VenueJurnal Ilmu Kesehatan · 2019
Typearticle
Language
FieldMedicine
TopicPublic Health and Nutrition
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineGynecology

Abstract

fetched live from OpenAlex

Introduction:.Iron deficiency is the most common cause of nutritional anemia. The highest incidence of anemia is found at the end of infancy and preschool. In the majority of families, mothers play an important role in the diet of children and the fulfillment of nutritional needs. One effort to improve the prevention behavior of anemia in children is the Calgary Family Intervention Model (CFIM). Method:.This research used preexperiment one group only with pre post test design. Samples were mothers with preschool children who attend kindergarten Muslimat Curungrejo Kepanjen Malang who meet the inclusion criteria of 22 (purposive sampling)). Calgary intervention/CFIM in prevention of anemia for 3 times meeting through home visits, each session for 50 minutes using the lecture, discussion, and counseling methods. The instrument used Food Frequency Quistionare (FFQ).Data analysis used Wilcoxon Sign Rank Test with 0.05. Result:.The result showed increased knowledge before (54,5 %) dan after (90.9%) with p value = 0.004. Discussion:.Intervention through home visits for 3 sessions by combining several methods play a role in increasing respondents' knowledge after the intervention. CFIM can improve mother's knowledge in the prevention of childhood anemia.

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity, Insufficient 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 score0.080
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0010.003
Open science0.0010.000
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0030.002

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 head0.015
GPT teacher head0.303
Teacher spread0.288 · 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
Published2019
Admission routes1
Has abstractyes

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