Effect of hydrolysed and regular dairy proteins on the texture, colour and microstructure of poultry meat emulsions
Bibliographic record
Abstract
1. The effects of 2% whole milk proteins, milk protein's two major components (caseinate and whey) and some of their fractions (beta-lactoglobulin and two hydrolysed whey proteins) were evaluated in a frankfurter-type product made from mechanically deboned chicken meat. 2. Adding caseinate, regular whey protein and the two whey protein hydrolysates (WPH-I and II) significantly reduced cooking loss compared to the control; lowest reduction was obtained with the two hydrolysates. 3. Caseinate and regular whey increased hardness, but WPH-I and II substantially reduced hardness, fracturability and springiness. 4. The more hydrolysed whey (8.5% vs 5.2%; WPH-II vs WPH-I, respectively) caused a greater disruption to texture, which could be explained by the light micrographs showing an interference with meat protein binding. 5. The most cost-effective ingredient tested here was the caseinate.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".