MétaCan
Menu
Back to cohort
Record W2930078758 · doi:10.30635/2415-0142.2018.04.4

Nutritive Values of Passion Fruit (Passiflora Species) Seeds and Its Role in Human Health

2018· article· en· W2930078758 on OpenAlexvenueno aff
Shiamala Devi Ramaiya, Japar Sidik Bujang, Muta Harah Zakaria

Bibliographic record

VenueJournal of Agriculture Food and Development · 2018
Typearticle
Languageen
FieldMedicine
TopicMedicinal Plant Extracts Effects
Canadian institutionsnot available
Fundersnot available
KeywordsPassifloraNutraceuticalPotassiumChemistryFood scienceProximateSodiumPhosphorusSunflowerBiologyHorticultureBotany

Abstract

fetched live from OpenAlex

This study focused on proximate composition and mineral content of edible seeds of three Passiflora species; P. edulis (Purple), P. quadrangularis and P. maliformis. The moisture content ranged 9.18±0.34% in P. edulis (Purple) to 11.09±0.40% in P. quadrangularis, and the ash content was higher in P. quadrangularis (2.35±0.13%). Among the Passiflora seeds, P. edulis (Purple) possessed higher protein, 12.71±0.10% and total dietary fiber, 43.76±0.64% with 72-74% major fiber fraction of insoluble dietary fiber. The lipid content of 29.65±0.41% also was higher in P. edulis (Purple) indicating that the seed was rich in oil content. Passiflora quadrangularis possessed a higher ash content which constitutes minerals such as sodium, 5.508±5.465 mg g-1 ; magnesium, 1.975±1.443 mg g-1 ; calcium, 2.363±3.269 mg g-1, and potassium, 2.425±2.500 mg g-1 that plays a prominent role in human health. Based on ordination with Principal component analyses (PCA), the Passiflora seeds properties when compared with maize, oats, flaxseed, sesame, soybean, almond, groundnut, sunflower and pumpkin, Passiflora plant seeds formed an independent group correlated with variables, i.e., fiber, sodium, and zinc. By-products from Passiflora seeds can be used for pharmaceutical and nutraceutical purposes.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.007

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.019
GPT teacher head0.269
Teacher spread0.250 · 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 designObservational
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

Citations29
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Agriculture Food and DevelopmentSame topicMedicinal Plant Extracts EffectsFrench-language works237,207