Effect of production factors on muscle fiber type and dimensions in the m. semimembranosus of crossbred steer carcasses
Bibliographic record
Abstract
The muscle fibers that have been examined in the study were affected by three different controlled factors: steroids, ractopamine and residual feed intake (RFI). By examining the effects of the controlled factors on cattle’s muscle fibers, it can be determined if they affect different meat properties, such as meat toughness, collagen solubility and muscle fiber quality. The research had been done specifically with m. semimembranosus (SM) of crossbred steers. Although some may be concerned with the health effects of steroids and other materials, no negative effects to the health of the cattle were observed after the use of steroids. This is because the hormones being introduced into the cattle’s body already exist in the animal. In addition, the same concept applies to humans who consume the meat, preventing harm the people who consume it. For this study, 48 crossbred angus steers were used, 12 for each of the different treatment groups. The control group consisted of no steroids and no ractopamine. The second group was not treated with steroid but with ractopamine. The third group was treated with steroids but no ractopamine. Finally, the fourth group was treated with both, the steroids and the ractopamine. For each SM muscle, 1-inch thick steaks were cut and from those steaks, 1cm3 cubes were cut. These cubes were frozen in dry ice acetone until they are ready to be sectioned. Cubes are placed in the cryostat and sliced into serial sections of 10µm. These serial sections are then mounted onto dry slide glass and stored in a freezer at -80ºC until they are to be stained. The staining process helps to identify the different types of muscle fibers in the samples. From the muscle fiber types, the average sizes of each muscle fiber is calculated to identify inconsistencies among the different treatment groups. Conclusions will be drawn based on the inconsistencies found (if any).
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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".