Formation of Soy Protein Isolate Cold‐set Gels: Protein and Salt Effects
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".