Effect of Crude Malva Nut Gum and Phosphate on Yield, Texture, Color, and Microstructure of Emulsified Chicken Meat Batter
Bibliographic record
Abstract
The effect of crude malva nut gum (CMG) use (0.0, 0.2, 0.6%) and sodium tripolyphosphate (TPP) addition (0.0, 0.5%) on the cook loss, texture, color, and microstructure of mechanically deboned chicken meat batters was studied. Increasing the level of CMG (a gum currently not used by the meat industry) in batters without TPP significantly increased yield. The batters with both CMG and TPP showed lower cook and fat losses compared with batters with CMG alone. Using 0.2 or 0.6% CMG and 0.5% TPP provided higher hardness values compared with using 0.6% CMG alone. The batter with 0.5% TPP and the batters with both CMG and TPP showed higher springiness compared with batters with CMG alone. Increasing the CMG level to 0.6% reduced the lightness and redness of the cooked products. Overall, the study demonstrated the beneficial effect of using CMG and TPP in improving the yield, stability, and texture of emulsified meat batters.
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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) | 0.001 | 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".