Feeding value of peas for backgrounding beef heifers
Bibliographic record
Abstract
Four diets in which peas progressively replaced barley [0% (0P), 30% (30P), 50% (50P), and 100% peas (100P)] and one in which canola meal (CM) replaced 10% of the barley, were fed to 90 beef heifers (initial weight 215.8 ± 13.8 kg). The heifers achieved average daily gains (ADGs) of 0.72, 0.80, 0.79, 0.83, and 0.76 kg d-1 on the five diets, respectively, with the difference between the 0P group and the 100P group being significant (P = 0.028). The total feed costs of gain were $0.786, 0.779, 0.799, 0.860, and 0.817 kg-1 for the five groups, respectively, with the cost of gain being significantly greater (P < 0.05) for the 100P group than for the 0P, 30P or 50P groups. The latter three were not significantly different from each other. Three rumen-cannulated steers (575 ± 56.3 kg) were used to estimate the degradability of the dry matter (DM) and N in the barley straw (BS), CM, barley grain (BG) and peas used in the feeding trial. The rumen undegradable protein (RUP) levels supplied by the five diets were 17.5, 19.0, 19.9, 21.5, and 22.5%, respectively, and all of them met the requirements of these cattle. The RUP content of peas ground through a 1-mm screen was lower than that of peas ground through 2- or 4-mm screens (P < 0.01), which were themselves not significantly different from each other (P = 0.67). The low RUP content of peas was not a limiting factor for growth in backgrounding cattle. Key words: Cattle, field peas, dry matter intake, feed conversion efficiency, rumen me
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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) | 0.000 | 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) | 0.001 | 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".