MétaCan
Menu
Back to cohort

Formation of Soy Protein Isolate Cold‐set Gels: Protein and Salt Effects

2005· article· en· W2147702746 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 Food Science · 2005
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicProteins in Food Systems
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsSoy proteinCalciumChemistryRheologySalt (chemistry)ChromatographyFood scienceChemical engineeringMaterials scienceOrganic chemistryComposite material

Abstract

fetched live from OpenAlex

ABSTRACT: The influence of protein and calcium concentration on soy protein cold‐set gel formation and rheology has been investigated. Cold‐set gels can be formed at soy protein concentrations from 6% to 9% and calcium concentrations from 10 to 20 mM. Gel properties can be modulated by changing the protein and/or CaCl 2 concentrations. An increase in CaCl 2 concentration from 10 to 20 mM increased gel opacity while an increase in protein concentration from 6% to 9% decreased opacity. Water‐holding capacity improved with increasing protein concentration and decreasing CaCl 2 concentration. The elastic modulus (G') increased with protein and calcium chloride concentrations. Microscopy revealed an increase in the diameters of aggregates and pores as CaCl 2 concentration increased and as protein concentration decreased. Cold‐set gels with a broad range of characteristics can be obtained from soy protein.

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)0.002
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 score0.022
Threshold uncertainty score0.174

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.022
GPT teacher head0.234
Teacher spread0.213 · 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