A dark, firm dry-like condition in turkeys condemned for cyanosis
Bibliographic record
Abstract
A case-control study (n = 130) was conducted on toms condemned for cyanosis. Color (CIE L*a*b*), pH, and physical characteristics were measured on the Pectoralis major at slaughter and after 24 h. Meat from carcasses condemned for cyanosis had dark, firm, dry-like traits. It was darker and redder and showed higher water-holding capacity, lower cooking loss, and higher gel strength than did controls. Perimortem pH was negatively correlated with the lightness (L*) of meat at the time of slaughter (r = -0.58) and at 24 h postmortem (r = -0.64), positively correlated with water-holding capacity (r = 0.73) and gel strength (r = 0.43) and negatively correlated with cooking loss (r = -0.50). Ultimate pH was negatively correlated with lightness (L*) of meat at slaughter time (r = -0.62) and at 24 h postmortem (r = 0.79) was positively correlated with water-holding capacity (r = 0.87) and gel strength (r = 0.61) and negatively correlated with cooking loss (r = -0.52). Tests based on pH and L* of the P. major were also assessed; tests based on pH had a sensitivity in the range of 0.79 to 0.89 and specificity (Sp) of 0.60 to 0.94. Tests based on L* showed sensitivity of 0.75 to 0.92, and specificity of 0.79 to 0.97. The repeatability of measurements varied from good (L*: rho = 0.6) to excellent (pH: rho = 0.92). Overall, turkey breast condemned for cyanosis showed dark, firm, dry-like traits. Tests based on color and pH are described as a means of identifying turkeys condemned for cyanosis.
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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 | 0.001 |
| 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) | 0.002 | 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 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".