Correlation of chicken breast quality and sensory attributes with chicken thigh quality and sensory attributes
Bibliographic record
Abstract
The purpose of this study was to characterize the relationship between chicken breast quality and sensory attributes with chicken thigh quality and sensory attributes. Whole chicken carcasses were fabricated into nine-piece traditional cut chicken in accordance with Canadian Food Inspection Agency and United States Department of Agriculture specifications. Following fabrication, right side breast and thigh samples were assessed for quality (pH, instrumental color, 48 h drip loss, and instrumental texture). Sensory attributes (tenderness, juiciness, flavor, and acceptability) using a trained sensory panel and cooking loss were assessed on the left side breast and thigh samples. Correlation coefficients between all traits were computed, and meaningful traits were further analyzed using regression. Breast and thigh pH were weakly correlated (r = 0.25; P = 0.07), breast and thigh color [lightness (L*), redness (a*), and yellowness (b*)] were weakly correlated (r ≤ 0.30; P ≥ 0.04), and breast and thigh 48 h drip loss were moderately correlated (r = 0.35; P = 0.01). Breast and thigh sensory tenderness were moderately correlated (r = 0.38; P < 0.01), whereas all other sensory parameters measured between breast and thigh samples were not significantly correlated (P ≥ 0.24). Overall, breast quality and sensory attributes were generally weakly correlated with thigh quality and sensory attributes.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".