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Record W1977114185 · doi:10.1021/jf904456r

Amino Acid Composition and Antioxidant Properties of Pea Seed (Pisum sativum L.) Enzymatic Protein Hydrolysate Fractions

2010· article· en· W1977114185 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

VenueJournal of Agricultural and Food Chemistry · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Hydrolysis and Bioactive Peptides
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsChemistryHydrolysateChromatographyUltrafiltration (renal)AntioxidantPeptideAmino acidHydrolysisLinoleic acidFractionationGlutathioneBiochemistryEnzymeFatty acid

Abstract

fetched live from OpenAlex

The amino acid composition and antioxidant activities of peptide fractions obtained from HPLC separation of a pea protein hydrolysate (PPH) were studied. Thermolysin hydrolysis of pea protein isolate and ultrafiltration (3 kDa molecular weight cutoff membrane) yielded a PPH that was separated into five fractions (F1-F5) on a C(18) reverse phase HPLC column. The fractions that eluted later from the column (F3-F5) contained higher contents hydrophobic and aromatic amino acids when compared to fractions that eluted early or the original PPH. Fractions F3-F5 also exhibited the strongest radical scavenging and metal chelating activities; however, hydrophobic character did not seem to contribute to reducing power of the peptides. In comparison to glutathione, the peptide fractions had significantly higher (p < 0.05) ability to inhibit linoleic acid oxidation and chelate metals. In contrast, glutathione had significantly higher (p < 0.05) free radical scavenging properties than the peptide fractions.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.032
Threshold uncertainty score0.344

Codex and Gemma teacher scores by category

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

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 head0.006
GPT teacher head0.190
Teacher spread0.184 · 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