Meat and sensory quality of major muscles from Angus, Charolais, and Angus crossbred steers with high and low residual feed intake
Bibliographic record
Abstract
Effects of residual feed intake (RFI) and genetic group on growth, carcass, and meat quality characteristics of bovine longissimus lumborum (LL), triceps brachii (TB), semimembranosus (SM), and gluteus medius (GM) muscles were investigated using 72 purebred Angus, purebred Charolais, and Angus crossbred steers (n = 24 per genetic group) classified as either high (inefficient) or low (efficient) RFI (n = 12 high and low RFI steers within genetic group). There was no RFI effect (P > 0.05) on growth, carcass, and meat quality measurements except high RFI steers had the highest dry matter intake (P < 0.05), and low RFI TB was rated as having reduced beef flavour intensity and sustained juiciness (P < 0.05). Purebred Angus and Charolais LL and GM had lower shear force values (P < 0.05) than Angus crossbreds and ageing reduced mean shear force values except in TB. For TB, SM, and GM, Angus crossbred steers had the highest mean beef flavour intensity scores, and Charolais SM and TB were less tender than those of Angus crossbred (P < 0.05). Overall, RFI did not influence most meat quality traits; therefore, low RFI animals may contribute to reducing feed costs or environmental impact without compromising meat quality and palatability.
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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 | 0.000 | 0.000 |
| 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) | 0.001 | 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".