Effects of milk powder and its components on texture, yield, and color of a lean poultry meat model system
Bibliographic record
Abstract
The effects of whole milk powder, 2 skim milk powders, caseinate, and 2 modified whey proteins (2% protein level in the final product) were evaluated in lean chicken meat batters and compared with controls with and without added lactose. All dairy proteins significantly (P<0.05) reduced cook losses when compared against the controls, with the 2 skim milk powders and modified whey-I showing the best results. Hardness and fracturability were also higher for all test batters compared with controls. Skim milk-II showed the highest fracturability value (21.9 vs. 7.1 N for the control) and was also found to be the most cost-effective ingredient for improving moisture binding and texture; skim milk-I and modified whey-I followed behind. Springiness and fracture distance were higher for all of the dairy proteins, except caseinate, indicating a positive contribution to the lean meat system's elasticity. In terms of color, adding the skim milk powders, modified whey-II, and whole milk powder resulted in lighter cooked meat batters as evidenced by the higher L* values and higher spectra curves.
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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 | 0.001 | 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".