PSIV-2 A comparison of feedlot growth and performance of beef x Holstein crossbred steers and Holstein steers
Bibliographic record
Abstract
Abstract Objectives were to compare feedlot performance and carcass traits of F1 beef × Holstein steers and Holstein steers. Angus or Limousin × Holstein crossbred [n = 27; age = 12 ± 3 months; body weight (BW) = 435 ± 8 kg] and Holstein (n = 20; age = 11 ± 2 months; BW = 400 ± 9 kg) steers were fed at the Pennsylvania Department of Agriculture Livestock Evaluation Center for 111 days. Feed intake was recorded using the GrowSafe Feed Intake Monitoring System (Model 4000E, GrowSafe Systems Ltd., Calgary AB, Canada). The diet contained corn silage, dried distillers grains, soybean meal, and cracked corn and was formulated to meet or exceed the requirements of beef cattle (NASEM, 2016). Growth performance variables of interest and carcass measurements were analyzed with the Mixed procedure of SAS (SAS 9.4; SAS Institute Inc., Cary, NC). USDA assigned quality grades (QG) and yield grades (YG) were analyzed the with GLIMMIX procedure of SAS. Breed was a fixed effect in all models. There were no differences (P > 0.05) between breeds in average daily gain or feed efficiency. Crossbreds exceeded Holsteins in initial (P < 0.01) and final BW (P = 0.01), dry matter intake (P = 0.03), hot carcass weight (P < 0.01), backfat (P = 0.03), and ribeye area (REA; P < 0.01). Thirty-five percent (35%) of the Holsteins received a QG of Choice or above while 74% of crossbreds graded USDA Choice or above (P = 0.01). However, 75% of Holsteins were YG 2 or lower while only 45% of crossbreds achieved YG 2 or less (P = 0.05). There was no improvement in efficiency when crossbreds were compared to Holsteins; however, carcasses from crossbreds were more likely to grade USDA Choice or above while yielding greater REA and backfat than Holsteins.
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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 | 0.001 | 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) | 0.002 | 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".