Effects of Adding Corn Dried Distiller Grains with Solubles (DDGS) to the Dairy Cow Diet and Effects of Bedding in Dairy Cow Slurry on Fugitive Methane Emissions
Bibliographic record
Abstract
The specific objectives of this experiment were to investigate the effects of adding 10% or 30% corn dried distillers grains with solubles (DDGS) to the dairy cow diet and the effects of bedding type (wood shavings, straw or peat moss) in dairy slurry on fugitive CH₄ emissions. The addition of DDGS10 to the dairy cow diet significantly increased (29%) the daily amount of fat excreted in slurry compared to the control diet. The inclusion of DDGS30 in the diet increased the daily amounts of excreted DM, volatile solids (VS), fat, neutral detergent fiber (NDF), acid detergent fiber (ADF) and hemicellulose by 18%, 18%, 70%, 30%, 15% and 53%, respectively, compared to the control diet. During the storage experiment, daily fugitive CH₄ emissions showed a significant increase of 15% (p < 0.05) for the slurry resulting from the corn DDGS30 diet. The addition of wood shavings and straw did not have a significant effect on daily fugitive CH₄ emissions relative to the control diet, whereas the addition of peat moss caused a significant increase of 27% (p < 0.05) in fugitive CH₄ emissions.
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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) | 0.001 | 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 | 0.001 | 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".