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Record W2625050666 · doi:10.1080/10408398.2017.1319795

Current trends and perspectives of bioactive peptides

2017· review· en· W2625050666 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCritical Reviews in Food Science and Nutrition · 2017
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Hydrolysis and Bioactive Peptides
Canadian institutionsMcGill University
Fundersnot available
KeywordsBiotechnologyBusinessHuman healthRisk analysis (engineering)Biochemical engineeringBiologyMedicineEnvironmental healthEngineering

Abstract

fetched live from OpenAlex

The remarkable growth of therapeutic peptide development in the past decade has led to a large number of market approvals and the market value is expected to hit $25 billion by 2018. This significant market increase is driven by the increasing incidences of metabolic and cardiovascular diseases and technological advancements in peptide synthesis. For this reason, the search for bioactive peptides has also increased exponentially. Many bioactive peptides from food and nonfood sources have shown positive health effects yet, obstacles such as the need to implement efficient and cost-effective strategies for industrial scale production, good manufacturing practices as well as well-designed clinical trials to provide robust evidence for supporting health claims continue to exist. Several other factors such as the possibility of allergenicity, toxicity and the stability of biological functions of the peptides during gastrointestinal digestion would need to be addressed.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.993
Threshold uncertainty score0.817

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.135
GPT teacher head0.428
Teacher spread0.293 · 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