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Record W4383955496 · doi:10.1002/fbe2.12057

Bioactive peptides: Synthesis, applications, and associated challenges

2023· article· en· W4383955496 on OpenAlexaff
Abrar Alzaydi, Rahul Islam Barbhuiya, Winny Routray, Abdallah Elsayed, Ashutosh Singh

Bibliographic record

VenueFood Bioengineering · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Hydrolysis and Bioactive Peptides
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsExploitPeptideComputational biologyAmino acidCombinatorial chemistryPeptide synthesisFractionationBiochemical engineeringBiotechnologyBiochemistryBiologyComputer scienceChemistryEngineeringOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Bioactive peptides (BPs) are chains of amino acids linked together by peptide bonds and arranged in a specific way. These peptides are important to human health and can be used in preserving food. The interest in BPs and its benefits has led to increased production from different food sources and advanced technology to extract them in their pure form. This review explores the subject of BP sources, their synthesis, and their application in various fields, including food and pharmaceuticals. Each source has its unique characteristics, types of peptides, and sequences. The sequence of each peptide extracted from different sources differs in their arrangement and effect on disease treatment. Despite the interest in BPs, challenges remain in their fractionation and purification. Further research is needed to fully exploit the potential of this diverse group of compounds for successful future applications.

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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.002

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 head0.017
GPT teacher head0.229
Teacher spread0.212 · 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

Citations36
Published2023
Admission routes1
Has abstractyes

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