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Record W2027087028 · doi:10.1111/ijfs.12275

Effect of <scp>pH</scp>, biopolymer mixing ratio and salts on the formation and stability of electrostatic complexes formed within mixtures of lentil protein isolate and anionic polysaccharides (κ‐carrageenan and gellan gum)

2013· article· en· W2027087028 on OpenAlexafffund
Felix N. A. Aryee, Michael T. Nickerson

Bibliographic record

VenueInternational Journal of Food Science & Technology · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicProteins in Food Systems
Canadian institutionsUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiopolymerChemistryPolysaccharideGellan gumCoacervateIonic strengthCarrageenanChitosanXanthan gumChromatographyChemical engineeringAqueous solutionOrganic chemistryRheologyPolymerFood science

Abstract

fetched live from OpenAlex

Summary Associative phase separation within lentil protein isolate (LPI), polysaccharide (κ‐carrageenan (κ‐CG) and gellan gum (GG)) mixtures was investigated as a function of pH (1.50–8.00) and mixing ratio (1:1–30:1; LPI/polysaccharide) by turbidity and electrophoretic mobility. Effects of salts (NaCl, KCl and CaCl 2 ) on complex stability were also studied as a function of ionic strength. Coacervation typically follows two pH ‐dependent forming events associated with the formation of soluble and insoluble complexes. The addition of polysaccharides to a LPI system (at all ratios) resulted in a significant drop in turbidity over the entire pH range and a shift in net neutrality to lower pH relative to LPI alone; where LPI aggregation was inhibited by repulsive forces between neighbouring polysaccharide chains. As the biopolymer mixing ratio increased, structure formation was less inhibited. The addition of salts resulted in the disruption of formed LPI/polysaccharide complexes.

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 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)0.001
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 score0.007
Threshold uncertainty score0.375

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.012
GPT teacher head0.235
Teacher spread0.223 · 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 teacher head, 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

Citations42
Published2013
Admission routes2
Has abstractyes

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