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Record W1981930609 · doi:10.3390/nu5093367

Flavonoid Bioavailability and Attempts for Bioavailability Enhancement

2013· review· en· W1981930609 on OpenAlexaff
Surangi H. Thilakarathna, H.P. Vasantha Rupasinghe

Bibliographic record

VenueNutrients · 2013
Typereview
Languageen
FieldMedicine
TopicPhytoestrogen effects and research
Canadian institutionsDalhousie University
Fundersnot available
KeywordsBioavailabilityFlavonoidFlavonolsIsoflavonesPharmacologyHuman healthFlavonesChemistryFood scienceAntioxidantBiologyBiochemistryMedicineBotany

Abstract

fetched live from OpenAlex

Flavonoids are a group of phytochemicals that have shown numerous health effects and have therefore been studied extensively. Of the six common food flavonoid classes, flavonols are distributed ubiquitously among different plant foods whereas appreciable amounts of isoflavones are found in leguminous plant-based foods. Flavonoids have shown promising health promoting effects in human cell culture, experimental animal and human clinical studies. They have shown antioxidant, hypocholesterolemic, anti-inflammatory effects as well as ability to modulate cell signaling and gene expression related disease development. Low bioavailability of flavonoids has been a concern as it can limit or even hinder their health effects. Therefore, attempts to improve their bioavailability in order to improve the efficacy of flavonoids are being studied. Further investigations on bioavailability are warranted as it is a determining factor for flavonoid biological activity.

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: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.107
GPT teacher head0.420
Teacher spread0.313 · 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

Citations772
Published2013
Admission routes1
Has abstractyes

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