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Record W1855248852 · doi:10.3968/3732

Health Benefits, Chemistry and Mechanism of Carica Papaya a Crowning Glory

2013· article· en· W1855248852 on OpenAlexvenueno aff
Ateeq Rahman

Bibliographic record

VenueAdvances in natural science/Advances in natural sciences · 2013
Typearticle
Languageen
FieldMedicine
TopicPapaya Research and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsCaricaFood sciencePillChemistryHorticultureToxicologyBiologyPharmacology

Abstract

fetched live from OpenAlex

Abstract Mini review article highlights about the health benefits, chemistry and mechanism of papaya. Fruit and vegetables cannot be equated to that promised by nutritional pills and supplements. Nutrition experts advocate generous intake of fruits for optimum health as these food items are loaded with all the benefits. Especially papaya fruits is goldmine of vitamins C, E, K, minerals and fiber and ideal to consume at least 4-5 servings in a day. Since they are in natural form, account for largest part of water and 100% bad cholesterol free, it’s much easier for the body to process and absorb the vitamins and minerals from the fresh fruit. The chemical action of acyltransferase is studied which is extracted from ripened papaya fruit and then benzyl alcohol is acylated to give benzylacetate.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.010
GPT teacher head0.346
Teacher spread0.336 · 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 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

Citations9
Published2013
Admission routes1
Has abstractyes

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