Time-dependent aggregation of casein micelle concentrates
Bibliographic record
Abstract
This research focused on understanding physical and chemical changes occurring to concentrated milk protein suspensions as a function of time. Skim milk (untreated and heat treated at 90°C for 10 min) was concentrated at 6 times the original volume using osmotic stressing, a noninvasive concentration method, maintaining the serum composition as close as possible to that of native milk. A protease inhibitor cocktail, with broad specificity for the inhibition of serine, cysteine, aspartic proteases, and aminopeptidases, was added in selected samples. Within 9 d of storage at 4°C, the apparent viscosity increased markedly for both unheated and heated concentrated milk, but not for those in the presence of protease inhibitors. However, only unheated milk showed a significant increase in the apparent diameter of the casein micelles. Matrix-assisted laser desorption-ionization time-of-flight mass spectrometry measurements indicated a significantly lower extent of proteolysis in heated than in unheated samples. The microstructure of the aggregates was observed using field emission scanning electron microscopy, and unheated samples clearly showed aggregation of casein micelles with storage time. In heated samples, aggregation was instead triggered by heat-induced protein-protein interactions.
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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 | 0.000 |
| 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 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".