Roaster Breast Meat Condemned for Cyanosis: A Dark Firm Dry-Like Condition?
Bibliographic record
Abstract
A case-control study (n = 68) of roaster chickens condemned for cyanosis was conducted. Color (CIE L*a*b*) and pH were measured at slaughter, and after 24 h aging on ice, at four predetermined sites of the Pectoralis major. Cyanotic carcasses (dark) had a higher pH than controls at the time of slaughter and at 24 h postmortem (P < 0.01). Perimortem pH was significantly correlated with pH at 24 h postmortem (r = 0.64) and also was correlated with lightness (L*) perimortem and postmortem (24 h; r = -0.36 and -0.50, respectively). Perimortem pH was not correlated with meat redness (a*) at slaughter time and after 24 h. Ultimate pH and lightness at 24 h postmortem were also correlated. Tests based on pH, L*, and a* of the P. major were assessed: the sensitivity and specificity at various cut-off points were, respectively, pH(6.3) = 76.47 and 88.24%, L*(41) = 91.18 and 79.41%, and a*(3) = 76.47 and 97.06%. The repeatability (p) of pH and color measurements was excellent and ranged from 0.87 to 0.98. Breast meat from roasters condemned for cyanosis had dark, firm, and dry (DFD)-like traits, and accurate tests based on color and pH could be described as a means of identifying chickens condemned for cyanosis.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".