Measured and modelled enteric methane emissions from beef cattle as affected by dietary crude protein of forage diets
Bibliographic record
Abstract
Methane emissions of 60 steers (321 ± 14 kg) fed isocaloric forage diets differing in crude protein (CP) content were measured at ambient daily temperatures averaging -17.5°C to determine if increased nitrogen status, measured by blood urea nitrogen (BUN), decrease CH4 as a percent of gross energy intake (% GEI) from backgrounding cattle. Average BUN concentrations (mmol L-1) were 0.81, 1.82, 3.05 and 3.51 (SE ± 0.108) for diets with 6.9% (low), 10.3% (adequate for rumen microbes), 11.1% (adequate for muscle growth) and 13.6% (excessive) CP respectively. Methane (% GEI) emissions decreased with increasing CP over time (P=0.04). Increasing CP content increased BUN levels and decreased methane emissions (% GEI). Although models were developed to predict CH4 emissions (% GEI) from steers and cows using a backward-elimination process, BUN accounted for only 0.7 to 5.7% of the partial R2 and therefore has limited value when modelling methane emission predictions.
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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) | 0.000 | 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".