Performance, digestibility, carcass characteristics, and blood parameters of backgrounding and finishing beef steers fed diets containing corn silage or barley straw with or without calcium oxide
Bibliographic record
Abstract
The effect of adding unhydrated calcium oxide (CaO) to corn silage (CS) or barley straw (BS) in a total mixed ration on growth performance, digestibility, blood parameters, and carcass characteristics was evaluated in backgrounding and finishing beef steers. Sixty Angus × beef steers were fed one of 4 diets, containing CS or BS (replacing CS at 12% diet dry matter (DM)) with or without 1% DM CaO replacing CaCO 3 . During backgrounding, CaO reduced ( P ≤ 0.04) weight gain, average daily gain, and gain:feed while only final body weight was reduced ( P = 0.05) during finishing. Feed efficiency and diet digestibility were greater ( P ≤ 0.05) for CS than BS diets. During backgrounding and finishing, CaO increased ( P = 0.02) crude protein and reduced ( P < 0.01) neutral detergent fibre digestibility, respectively. Adding CaO to the backgrounding diet increased ( P ≤ 0.01) serum amyloid-A and serum cortisol concentrations. The CaO reduced ( P ≤ 0.02) hot carcass weight and dressing percentage compared to control, while BS reduced ( P ≤ 0.02) ribeye area and grade fat compared to CS. Substituting BS for CS and including CaO decreased feed efficiency, carcass yield, and income over feed cost in feedlot steers.
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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".