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Record W4200259503 · doi:10.1002/star.202100251

Resistant Starch in Wheat‐, Barley‐, Rye‐, and Oat‐Based Foods: A Review

2021· review· en· W4200259503 on OpenAlexaff
Si Nhat Nguyen, Pamela Drawbridge, Trust Beta

Bibliographic record

VenueStarch - Stärke · 2021
Typereview
Languageen
FieldNursing
TopicFood composition and properties
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsFood scienceStarchResistant starchSecaleMashingWhole grainsWheat flourDietary fiberExtrusion cookingPostprandialFermentationHealth benefitsFood processingChemistryBiologyBiotechnologyAgronomyMedicineTraditional medicine

Abstract

fetched live from OpenAlex

Abstract Resistant starch (RS) has received a lot of attention from plant, food, and clinical scientists because of its demonstrated health benefits. In this review, the presence and formation of RS from grain to food is investigated with a focus on wheat‐, barley‐, rye‐, and oat‐based foods. The impact of ingredients (lipids and proteins) and food processing on the formation of RS in grain‐based food is examined. RS has been found to develop in various processes during food manufacturing (baking, extrusion, fermentation, and mashing) and its content could be affected by changing the operating parameters. In addition, the formation of RS during the preservation of starchy foods as well as the techniques to mitigate this phenomenon is discussed. The introduction of RS into cereal‐based foods (bread, cookie, biscuit, and pasta) enhances the product fiber content and induces some changes in the technological parameters, texture, color, and sensory properties of final products. Overall, the acceptability of RS‐incorporated foods is well liked and has the potential to elicit positive effects on gut health and postprandial glycemia.

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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.099
GPT teacher head0.374
Teacher spread0.274 · 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

Citations10
Published2021
Admission routes1
Has abstractyes

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