Study of the Effect of Soy Proteins on the Acid-Induced Gelation of Casein Micelles
Bibliographic record
Abstract
The objective of this research was to understand whether addition of soy protein to milk protein affects the properties of acid-induced casein gels. Different samples were prepared by suspending casein micelles pellets in milk serum containing soy proteins or whey proteins as well as mixtures of the two proteins. Glucono-delta-lactone was added, and the changes in apparent size (in diluted systems) as well as the viscoelastic properties of the mixtures were measured. Size exclusion chromatography was also carried out to characterize the soluble phase of the various mixtures before and after heating. Soy protein affected the gelation of the mixtures; however, not to the same extent as whey proteins, which dominated formation of the network in soy-whey-casein systems. It was concluded that, up to a critical ratio of soy/whey proteins, soy proteins can be incorporated in the mix without a significant change in structure of the casein gels.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".