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Record W3105363178 · doi:10.32763/juke.v13i2.191

Pemberian Ekstrak Kacang Hijau (Phaseolus Radiatus) terhadap Peningkatan Hemoglobin dan Ferritin pada Wistar Putih Anemia

2020· article· id· W3105363178 on OpenAlexaff
Heni Wijayanti

Bibliographic record

VenueJurnal Kesehatan Poltekkes Ternate · 2020
Typearticle
Languageid
FieldAgricultural and Biological Sciences
TopicFood and Agricultural Sciences
Canadian institutionsInterface Biologics (Canada)
Fundersnot available
KeywordsTraditional medicineMedicineFerritinHemoglobinGynecologyInternal medicine

Abstract

fetched live from OpenAlex

Kacang hijau, selain mengandung protei, karbohidrat dan lemak juga mengandung zat besi dan vitamin C yang terbukti dapat memperbaiki anemia pada wanita hamil. Kadar zat besi yang tinggi berpotensi meningkatkan produksi ROS reaksi fenton. Penelitian ini untuk membuktikan bahwa pemberian ekstrak kacang hijau dapat meningkatkan kadar Hb dan kadar Ferritin pada tikus wistar putih.Penelitian ini menggunakan rancangan Post Test Only Control Group Design.Sebanyak 25 ekor tikus wistar dibagi menjadi 5 kelompok yaitu kelompok normal (Nor-G), kelompok control negative(Neg-G)dan kelompok perlakuan yang mendapatkan ekstrak kacang hijau 0,18g (GP-0,18), 0,36g (GP-0,36) dan 0,72g(GP-0,72). Diet rendah Fe dan ekstrak kacang hijau diberikan semala 14 hari. Kadar Hb diukur dengan metode Sahli dan Kadar Ferritin menggunakan Kit Immulite Ferritin. Kadar Hd dan ferritin pada kelompok yang mendapatkan ekstrak kacang hijau 0,18g (75,56), 0,36g (90,98) dan 0,72g (95,87) lebih tinggi bermakna, p<0,05. Hasil penelitian ini menunjukkan bahwa pemberian ekstrak kacang hijau terbukti meningkatkan kadar Hb dan Kadar Ferritin.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.765
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.002
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0030.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.022
GPT teacher head0.226
Teacher spread0.203 · 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 teacher head, not a consensus.

Study designBench or experimental
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

Citations2
Published2020
Admission routes1
Has abstractyes

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