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Record W3046497273 · doi:10.1093/nutrit/nuz085

Emerging science on benefits of whole grain oat and barley and their soluble dietary fibers for heart health, glycemic response, and gut microbiota

2019· review· en· W3046497273 on OpenAlexaff
Susan M. Tosh, Nicolas Bordenave

Bibliographic record

VenueNutrition Reviews · 2019
Typereview
Languageen
FieldNursing
TopicFood composition and properties
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsPostprandialFood scienceWhole grainsDietary fibreGlycemicGut floraDietary fiberGlycemic indexCoronary heart diseaseDiabetes mellitusFunctional foodType 2 diabetesBiologyChemistryMedicineBiochemistryInternal medicineEndocrinology

Abstract

fetched live from OpenAlex

The aim of this work is to review the major mechanisms by which consumption of whole grain oats and barley, and β-glucans, reduces the risk of coronary heart disease, type 2 diabetes, and other noncommunicable chronic conditions. These effects have been predominantly explained by the role of soluble dietary fibers and smaller bioactive compounds, such as phenolic compounds, in oats and barley. These help to reduce the level of serum low-density lipoprotein cholesterol, decreasing postprandial blood glucose and modulating gut microbiota. In the present review, the role of viscosity development of the intestinal content by β-glucans in these mechanisms is discussed, as well as the impact of processing conditions altering the composition or the physicochemical characteristics of β-glucans.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.087
GPT teacher head0.352
Teacher spread0.265 · 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

Citations173
Published2019
Admission routes1
Has abstractyes

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