Effect of variety and level of inclusion of barley silage selected for varying neutral detergent fiber digestibility on ruminal fermentation and nutrient digestibility in feedlot heifers fed backgrounding and finishing diets
Bibliographic record
Abstract
Two metabolism studies were conducted to evaluate the effect of variety and level of inclusion of barley silage on ruminal fermentation and total tract nutrient digestibility using beef heifers fed backgrounding (Study 1) and finishing (Study 2) diets. Both studies were 4 × 4 Latin square designs with a 2 × 2 factorial arrangement (barley varieties, CDC Cowboy and Xena; levels of inclusion, LOW and HIGH). Barley varieties did not vary in 30 h neutral detergent fiber (NDF) digestibility and averaged 37.1% ± 1.86% (% of NDF) across varieties. Heifers fed CDC Cowboy had greater (P = 0.05) mean ruminal pH and a lower (P = 0.01) duration under pH 5.8 relative to those fed Xena in Study 1, whereas heifers fed HIGH-silage diets had lower (P = 0.05) duration under ruminal pH 5.8 than those fed LOW-silage diets in Study 2. Variety of barley had minimal impact on ruminal fermentation and total tract nutrient digestibility in heifers fed barley silage, although high NDF content decreased energy intake. High NDF barley varieties and greater inclusion levels also increased ruminal pH which may improve total tract fiber digestibility in heifers fed finishing diets.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".