Effects of regular and modified starches on cooked pale, soft, and exudative; normal; and dry, firm, and dark breast meat batters
Bibliographic record
Abstract
The effects of potato and tapioca starches (regular and modified) on the texture, yield, and microstructure of pale, soft, and exudative (PSE); normal; and dark, firm, and dry (DFD) chicken breast meats were studied. Cook yield and fracture force were higher in DFD than in normal and PSE meat. All starches significantly improved yield with modified tapioca showing the best results. Light microscopy showed even distribution and gelatinization of large potato starch granules and small tapioca granules. Addition of starches to the normal meat (46 < L* < 53, 5.9 < pH < 6.1) resulted in higher modulus of rigidity (G') values above 60 degrees C. During cooling, this trend continued as all starches provided significantly higher G' values compared with the control; regular and modified potato resulted in higher G' values than the tapioca starches. Overall, starch addition can compensate for part of the meat protein functionality lost in PSE meat.
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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".