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Record W2969787360 · doi:10.21746/aps.2019.8.8.2

A review on chemical composition and pharmacological properties of Cocos nucifera (L.) oil and water

2019· review· en· W2969787360 on OpenAlexaff
Reetu Dubey, Sanjukta Rajhans, Dhruv Pandya, Archana Mankad

Bibliographic record

VenueAnnals of Plant Sciences · 2019
Typereview
Languageen
FieldChemistry
TopicCoconut Research and Applications
Canadian institutionsImpact
Fundersnot available
KeywordsCocos nuciferaArecaceaeCoconut oilTraditional medicineChemical constituentsPalm oilBotanyChemistryPalmBiologyFood scienceMedicineChromatography

Abstract

fetched live from OpenAlex

Cocos nucifera  (L.) (Coconut) is a palm tree belonging to the family Arecaceae, a native to Philippines and Malaysia. It is considered as one of the most useful plants for humankind because of its nutritive value and economic importance. Cocos nucifera oil and water contents are rich in a variety of chemical constituents  and posses varied potent therapeutic and pharmacological properties such as anti-microbial, anti-inflammatory, anti-oxidant, anti-malarial, anti-cardioprotective, anti-parasitical, analgesic activity, antineoplastic, cooling agent, etc. In this article, we review the chemical constituents and pharmacological properties of Cocos nucifera oil and water.

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)0.000
metaresearch head score (Gemma)0.000
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: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.002

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 head0.318
GPT teacher head0.426
Teacher spread0.108 · 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
GenreReview

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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