Short communication: Effects of feeding sweet sorghum silage on milk production of lactating dairy cows
Bibliographic record
Abstract
The objective of this study was to determine the feeding value of sweet sorghum silage (SS) for dairy cows compared with alfalfa silage (AS). Two diets were formulated with a 50:50 forage:concentrate ratio. Sweet sorghum silage and AS constituted 70% of the forage in each diet (dry matter basis). Twelve lactating Holstein cows in early lactation were used in a crossover experiment. Relative to AS, SS contained 58% more neutral detergent fiber and 36.6 and 72.7% less acid detergent lignin and crude protein, respectively. Milk yield (33.0 vs. 36.7 kg/d) was lower for cows fed SS than for those fed AS. However, dry matter intake, energy-corrected milk, and feed efficiency were similar for both dietary treatments. Replacing AS with SS increased concentrations of milk fat (4.44 vs. 3.80%) and total solids (13.31 vs. 12.88%) and reduced concentrations of milk lactose (4.55 vs. 4.61%), milk solids-not-fat (8.88 vs. 9.08%), and milk urea nitrogen (10.0 vs. 14.0 mg/dL). We concluded that replacing AS with SS had negative effects on milk yield, whereas dry matter intake, energy-corrected milk, and milk efficiency were similar.
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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 | 0.000 | 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".