Methane production and energy partitioning in sheep fed <i>Andropogon gayanus</i> grass ensiled at three regrowth stages
Bibliographic record
Abstract
Ribeiro Jr., G. A., Teixeira, A. M., Velasco, F. O., Faria Jr., W. G., Jayme, D. G., Maurício, R. M., Gonçalves, L. C. and McAllister, T. A. 2015. Methane production and energy partitioning in sheep fed Andropogon gayanus grass ensiled at three regrowth stages. Can. J. Anim. Sci. 95: 103–110. This study was undertaken to evaluate the effect of harvesting Andropogon gayanus at different regrowth stages (56, 84 and 112 d) on the nutritional value of silage and CH4 emissions from sheep. Rams (n=18) were adapted to silages for 21 d after which intake and digestibility were measured over 5 d in a completely randomized design (six rams/treatment). Heat production and methane emissions from each ram were measured in a respiration chamber over 24 h. Silage dry matter (DM; 54.4 g kg−1 BW0.75 d−1) intake was not influenced (P>0.05) by silage regrowth stage, but apparent DM digestibility linearly decreased (P<0.05) from 526 to 380 g kg−1 with increasing regrowth. Energy lost as a percent of gross energy intake (GEI) linearly increased with longer regrowth, yet no effect on CH4 losses (as% GEI; g kg−1 DM; g kg−1 digestible DM) or heat production were observed. Ensiling A. gayanus grass at an earlier regrowth stage (56 d) will improve silage quality, but improvements in the energetic value are not due to a reduction in enteric CH4 emissions as a% GEI.
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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".