Establishment of consumer thresholds for beef quality attributes
Bibliographic record
Abstract
Acceptability threshold values for Warner-Bratzler shear (WBS) and trained sensory panel attributes were determined through regression analyses against consumer scores for overall tenderness, juiciness, flavour desirability and overall palatability for both the longissimus lumborum (LL) and semimembranosus (SM) muscles. Although consumers were not as sensitive to changes in tenderness as trained panellists, the relationship between consumer scores and trained panellist scores was moderate (r value = 0.64; P = 0.001). Based on the 50% confidence levels for WBS (7.85 and 8.15 kg for the LL and SM, respectively), 20% of LL steaks and 28% of SM roasts collected from commercial abattoirs and aged 6 d exceeded these thresholds. When assessed on the basis of subjective sensory panel scores for overall tenderness, 25.3% of LL steaks and 39.9% of SM roasts exceeded the 50% confidence level. Clearly, without intervention strategies beyond 6 d of aging, there was a significant portion of beef steaks and roasts which did not meet consumer expectations for tenderness. The fact there was a very poor relationship between tenderness in the LL and SM muscles suggests strategies used by industry to improve tenderness may need to be muscle specific. Key words: Beef quality, consumer, threshold, tenderness, Warner-Bratzler shear
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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 | 0.002 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".