Performance of growing and finishing cattle supplemented with a slow-rlease urea product and urea
Bibliographic record
Abstract
Two growth trials were conducted to study the performance of Angus Crossbred steers supplemented with a slow-release urea product (Optigen® 1200, O) and urea (U). The base diets were composed of corn silage alone during the growth period and corn silage plus cracked corn during the finishing period. Trial 1 consisted of 40 animals [272 ± 4 kg body weight (BW)] individually fed the base diets and six treatments, which were based on corn silage alone and cracked corn supplemented with U or O to supply 50 (U 50 , O 50 ) or 100% (U 100 , O 100 ) of the ruminal N deficiency (U 50 , O 50 , U 100 , and O 100 ) as predicted by the Cornell Net Carbohydrate and Protein System (CNCPS), or with U and O each supplying half of the CNCPS predicted N deficiency (U 25 O 25 ). In trial 2, 120 pen-fed animals (241 ± 7 kg BW) received the base diets and four combinations of U and O ( U 100 O 0 , U 66 O 34 , U 34 O 66 , and U 0 O 100 ), which were designed to supply 100% of the ruminal N deficiency predicted by the CNCPS. In trial 1, no differences (P > 0.05) in performance were observed between the U 100 and O 100 treatments, but animals in the U 50 treatment had a greater average daily gain (ADG) (P < 0.05) and feed conversion (P < 0.05) than animals on O 50 treatment. In trial 2, combinations of U and O did not affect animal performance (P > 0.05). No differences were observed in carcass characteristics and predicted carcass and empty body fat for both trials (P > 0.05). We concluded there was no improvement in animal performance when urea was substituted by a slow-release urea/NH 3 product at levels normally found in feedlot cattle diets. Key words: Cornell net carbohydrate and protein system, modeling, nutrition, growth, non-protein nitrogen
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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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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".