Effects of pre‐emulsifying fat/oil on meat batter stability, texture and microstructure
Bibliographic record
Abstract
Summary The effects of pre‐emulsified beef fat and canola oil (CO) (25%) with Tween 80 (T‐80) or sodium caseinate (SC) were studied in beef meat batters prepared at three protein levels (9%, 12% and 15%). Raising meat protein level to 15% resulted in low emulsion stability of products prepared with CO. Using pre‐emulsified beef fat with Tween 80 (BF‐T80) showed significantly higher fat and water losses at all protein levels. There were no differences in fat and water losses between pre‐emulsified beef fat and CO when SC was used at the 9% and 12% protein levels compared to the controls (non pre‐emulsification). Light microscopy revealed fat globule coalescence in the CO meat batters prepared with 15% protein and BF‐T8 treatments, as well as formation of fat channels and more protein aggregation; both resulted in lower emulsion stability. Using SC to emulsify fat/oil produced a finer dispersion of fat globules compared to all the other treatments.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".