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Record W4388157297 · doi:10.37231/jimk.2022.23.3.700

An Analysis on Antioxidant Drinks during the Prophet’s Time in Makkiyah Context

2022· article· en· W4388157297 on OpenAlexaff
Nurul Mukminah Zainan Nazri, Ahmad Nur Ikram Mansor

Bibliographic record

VenueJurnal Islam dan Masyarakat Kontemporari · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Islamic Studies
Canadian institutionsNGC Aerospace (Canada)
Fundersnot available
KeywordsPalatabilityContext (archaeology)Content analysisQualitative analysisDescriptive statisticsFood scienceTraditional medicineQualitative researchMedicineSocial scienceSociologyGeographyChemistryMathematicsStatistics

Abstract

fetched live from OpenAlex

The purpose of this paper was to analyze antioxidant drinks during the prophet’s Muhammad time in makkiyah context. Prophet Muhammad lived in Makkah for 13 years with its society and these years known as makkiyah context. In recent times, the Makkan society and other societies of the world were reported to have an unhealthy diet. This paper focuses on the diet in makkiyah context during the prophet’s time to understand a well-balanced diet as an exemplary dietary model for societies worldwide. The method used in this qualitative study is content analysis. Data collected through content and document analysis are thematically analyzed using descriptive and analytical methods. Findings demonstrate that milk and honey were among Makkah’s familiar drinks and the Quranic ayāhs on them represent specific themes. The implication of this study establishes that the drinks during the prophet’s time in makkiyah context contain beneficial antioxidant compounds. The intake of milk and honey is recommended in the daily diet because they serve as the best types of drinks owing to their health benefits and palatability.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0040.002
Scholarly communication0.0020.002
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.018
GPT teacher head0.294
Teacher spread0.276 · 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 designNot applicable
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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