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Record W4294839590 · doi:10.18280/ijdne.170419

The Influence of Giving Biscuits of Yellow Pumpkin Seed and Capsule of Moringa Leaves on the Level of C-Reactive Protein on Pregnant Women

2022· article· en· W4294839590 on OpenAlexvenueno aff
Musaidah Musaidah, Aminuddin Syam, Atjo Wahyu, Veni Hadju, Toto Sudargo, Andi Zulkifli Abdullah, Muhammad Syafar, Zainal Zainal, Ridha Hafid, Rosdiana Syukur

Bibliographic record

VenueInternational Journal of Design & Nature and Ecodynamics · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMoringa oleifera research and applications
Canadian institutionsnot available
Fundersnot available
KeywordsMoringaTraditional medicineMedicineFood scienceBiology

Abstract

fetched live from OpenAlex

Pregnant women are likely to have the option of receiving supplementary nourishment in the form of pumpkin seed biscuits and Moringa leaves. The purpose of this study is to see how Pumpkin Seed Biscuits and Moringa Leaf Capsules affect C-Reactive Protein (C-RP) levels in pregnant women at the Stunting Locus, Bone Regency. A Quasi-Experimental method, also known as a field trial. The Non-Randomized Pre-Test - Post Test Group Design was adopted for the research design. Participants in this study were separated into two groups: group I was given pumpkin seed biscuits and a blood-added tablet, and group II was given Moringa leaf extract capsule supplements and a blood-added tablet, with a total of 30 persons in each group. The intervention lasted 90 days and included both a pre-test and a post-test. The levels of C-Reactive Protein in group I (Pumpkin Seed Biscuits) decreased by -0.11±0.04 g/mL. The decrease in C-Reactive Protein levels in group II (Moringa Leaf Extract) was -0.09±0.04 g/mL. Moringa capsules (p=0.001) and pumpkin seed biscuits (p=0.001) had an impact on reducing C-RP levels in pregnant women. Supplemental feeding of pumpkin seed biscuits and Moringa leaf extract capsules can enhance and improve the health condition of pregnant women by lowering C-Reactive Protein levels.

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 categoriesnone
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 score0.589
Threshold uncertainty score0.142

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.033
GPT teacher head0.259
Teacher spread0.227 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Design & Nature and EcodynamicsSame topicMoringa oleifera research and applicationsFrench-language works237,207