Effect of α-tocopherol tissue levels on beef quality
Bibliographic record
Abstract
To evaluate meat quality of beef with different α-tocopherol tissue levels, 55 feedlot steers were fed a barley-based finisher diet with four vitamin E supplementation levels (0, 350, 700 and 1400 IU DL-α-tocopheryl acetate/animal per day) for 120 days. Although the increase in oxidation levels overtime was much smaller (P < 0.001) in the high-medium and high groups, α-tocopherol tissue levels did not affect (P > 0.05) pH, proximate analysis, drip and cooking losses, and shear force of steaks. No effect of α-tocopherol tissue levels was found in retail evaluation of steaks after a short ageing time of 6 days, but with 21 days of ageing, a delay in formation of metmyoglobin (P = 0.008) was observed in steaks with higher tissue levels of α-tocopherol. Similar results were found for ground beef (25% fat) prepared from 6-day aged meat. Thus, higher α-tocopherol tissue levels protect ground beef and long-aged steaks from discolouration and lipid oxidation.
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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".