A comparison of the heat stability of fresh milk protein concentrates obtained by microfiltration, ultrafiltration and diafiltration
Bibliographic record
Abstract
The objective of this work was to evaluate the impact of changes during membrane filtration on the heat stability of milk protein concentrates. Dairy protein concentrates have been widely employed in high protein drinks formulations and their stability to heat treatment is critical to ensure quality of the final product. Pasteurized milk was concentrated three-fold by membrane filtration, and the ionic composition was modified by addition of water or permeate from filtration (diafiltration). Diafiltration with water did not affect the apparent diameter of the casein micelles, but had a positive effect on heat coagulation time (HCT), which was significantly longer (50 min), compared to the non diafiltered concentrates (about 30 min). UHT treatments increased the particle size of the casein micelles, as well as the turbidity of retentates. Differences between samples with and without diafiltration were confirmed throughout further analysis of the protein composition of the unsedimentable fraction, highlighting the importance of soluble protein composition on the processing functionality of milk concentrates.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 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".