Tenderness and sensory attributes of 11 muscles from carcasses within the Canadian cull cow grades
Bibliographic record
Abstract
The eating quality and shear force of meat from mature beef carcasses graded within the Canadian grading system were compared with youthful carcasses. Eleven muscles were obtained from mature-graded carcasses with >50% ossification (D1, D2, D3, and D4; n = 84) and youthful carcasses with <50% ossification [over 30 mo (OTM); n = 18, and under 30 mo (UTM) of age; n = 18, based on dentition]; muscles were aged 14 d prior to sensory and shear force analysis. Many muscles from mature-graded carcasses were juicier than UTM, however, most were less tender (P < 0.05). Psoas major was tender, particularly in D1 and OTM carcasses where tenderness measures were not significantly different from UTM (P > 0.05). Shear force values from the infraspinatus of D1 and OTM carcasses were not different from UTM. Flavour intensity was higher in several muscles from D1, D2, and D4 carcasses (P < 0.05), whereas flavour intensity was lower in several muscles from D3 (P < 0.05). Changes to eating quality attributes differed among mature grades; therefore, processors could potentially use the information presented here as a guide for utilizing cuts which retain high eating quality and separating those requiring tenderness intervention to reach consumer acceptability.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".