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Record W4387360174 · doi:10.1021/acs.jafc.3c02304

Impact of Oat (<i>Avena sativa</i> L.) on Metabolic Syndrome and Potential Physiological Mechanisms of Action: A Current Review

2023· review· en· W4387360174 on OpenAlexaboutno aff
Lin Li, Ruiyuan Zhang, Yichen Hu, Hongdan Deng, Xu Pei, Fang Liu, Chen Chen

Bibliographic record

VenueJournal of Agricultural and Food Chemistry · 2023
Typereview
Languageen
FieldMedicine
TopicLiver Disease Diagnosis and Treatment
Canadian institutionsnot available
FundersChina Scholarship Council
KeywordsAvenaMetabolic syndromeDyslipidemiaBiologyObesityBiotechnologyFood scienceAgronomyMedicineEndocrinology

Abstract

fetched live from OpenAlex

Oat ( Avena sativa L.), an annual herbaceous plant belonging to the Gramineae family, is widely grown in various regions including EU, Canada, America, Australia, etc . Due to the nutritional and pharmacological values, oats have been developed into various functional food including fermented beverage, noodle, cookie, etc . Meanwhile, numerous studies have demonstrated that oats may effectively improve metabolic syndrome, such as dyslipidemia, hyperglycemia, atherosclerosis, hypertension, and obesity. However, the systematic pharmacological mechanisms of oats on metabolic syndrome have not been fully revealed. Therefore, in order to fully explore the benefits of oat in food industry and clinic, this review aims to provide up-to-date information on oat and its constituents, focusing on the effects on metabolic syndrome.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.060
GPT teacher head0.337
Teacher spread0.277 · 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 designSystematic review
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

Citations12
Published2023
Admission routes1
Has abstractyes

Explore more

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