High-fibre high-lipid by-product pellets containing calcium oxide-treated oat hulls as a partial replacement for barley grain in finishing diets for beef cattle
Bibliographic record
Abstract
Two studies were conducted to evaluate the effects of treating oat hulls with calcium oxide (CaO) prior to inclusion in a high-lipid by-product pellet (HLP) on dry matter intake (DMI), ruminal fermentation, and total-tract digestibility (Study 1) and growth performance (Study 2). In Study 1, six ruminally cannulated heifers were used in a replicated 3 × 3 Latin square design. Study 2 used 210 steers in 21 pens in a 113 d finishing study. Dietary treatments for both studies included a barley-based control diet (CON), a diet where HLP partially replaced barley grain (NT-HLP), and a diet where HLP contained oat hulls treated with 7.5% CaO [dry matter (DM) basis; CaO-HLP]. For Study 1, DMI and ruminal pH were not affected. Apparent total-tract digestibility of DM and organic matter (OM) were greater (P < 0.05) for CON than NT-HLP and CaO-HLP. In Study 2, final body weight tended to be greater for NT-HLP and CaO-HLP than CON (P = 0.065). For CaO-HLP and NT-HLP, DMI was greater than CON (P < 0.01), but average daily gain (ADG) (2.0 kg d−1) and gain:feed (G:F) (0.16 kg kg−1) were not different. Thus, HLP can partially replace barley grain in finishing diets without negatively affecting ruminal fermentation or growth performance, but treatment with CaO has no effect.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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 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".