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Record W2948753446 · doi:10.3390/foods8060199

Protein Digestibility of Cereal Products

2019· article· en· W2948753446 on OpenAlexaff
Iris J. Joye

Bibliographic record

VenueFoods · 2019
Typearticle
Languageen
FieldNursing
TopicFood composition and properties
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsProtein qualityProtein digestibilityDigestion (alchemy)Food scienceAmino acidStorage proteinChemistryBiochemistryBiotechnologyBiologyChromatographyGene

Abstract

fetched live from OpenAlex

Protein digestibility is currently a hot research topic and is of big interest to the food industry. Different scoring methods have been developed to describe protein quality. Cereal protein scores are typically low due to a suboptimal amino acid profile and low protein digestibility. Protein digestibility is a result of both external and internal factors. Examples of external factors are physical inaccessibility due to entrapment in e.g., intact cell structures and the presence of antinutritional factors. The main internal factors are the amino acid sequence of the proteins and protein folding and crosslinking. Processing of food is generally designed to increase the overall digestibility through affecting these external and internal factors. However, with proteins, processing may eventually also lead to a decrease in digestibility. In this review, protein digestion and digestibility are discussed with emphasis on the proteins of (pseudo)cereals.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.021
GPT teacher head0.249
Teacher spread0.228 · 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 designBench or experimental
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

Citations402
Published2019
Admission routes1
Has abstractyes

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