MétaCan
Menu
Back to cohort
Record W2054508938 · doi:10.1021/jf802643n

Effect of pH, Salt, and Biopolymer Ratio on the Formation of Pea Protein Isolate−Gum Arabic Complexes

2009· article· en· W2054508938 on OpenAlexaff
Shuanghui Liu, Nicholas H. Low, Michael T. Nickerson

Bibliographic record

VenueJournal of Agricultural and Food Chemistry · 2009
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicProteins in Food Systems
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsBiopolymerGum arabicSalt (chemistry)ChemistryArabicFood scienceWhey protein isolateChromatographyOrganic chemistryWhey proteinPolymer

Abstract

fetched live from OpenAlex

Turbidity measurements were used to study the formation of soluble and insoluble complexes between pea protein isolate (PPI) and gum arabic (GA) mixtures as a function of pH (6.0-1.5), salt concentration (NaCl, 0-50 mM), and protein-polysaccharide weight mixing ratio (1:4 to 10:1 w/w). For mixtures in the absence of salt and at a 1:1 mixing ratio, two structure-forming transitions were observed as a function of pH. The first event occurred at a pH of 4.2, with the second at pH 3.7, indicating the formation of soluble and insoluble complexes, respectively. Sodium chloride ( 7.5 mM) due to substantial PPI aggregation. The pH at which maximum PPI-GA interactions occurred was 3.5 and was independent of NaCl levels. As PPI-GA ratios increased, structure-forming transitions shifted to higher pH.

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)0.002
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: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.011
GPT teacher head0.200
Teacher spread0.190 · 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

Citations232
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Agricultural and Food ChemistrySame topicProteins in Food SystemsFrench-language works237,207