Short communication: Performance of lactating dairy cows fed pearl millet grain
Bibliographic record
Abstract
Fifteen multiparous Holstein cows were used in a 3 x 3 Latin square experiment to determine the effects of feeding pearl millet grain on feed intake, milk yield, and milk composition of lactating dairy cows. Three isonitrogenous diets with a 57:43 forage:concentrate ratio were formulated. Diets contained 30% corn, 30% pearl millet, or 31% corn and pearl millet mixed 1:1 (wt/wt). Three lactating Holstein cows fitted with ruminal cannulas were used to determine the effects of dietary treatments on ruminal fermentation parameters. Dry matter intake and energy-corrected milk were similar for all dietary treatments and averaged 23.8 and 33.5 kg/d, respectively. Dry matter intake (% of BW) was unaffected by dietary treatments and averaged 3.40%. Milk fat, protein, lactose, and total solids concentrations were not influenced by grain type. Ruminal NH(3)-N concentration was unaffected by dietary treatments. However, ruminal pH tended to be lower for cows fed pearl millet than those fed corn and pearl millet mix. It was concluded that pearl millet grain can replace corn in dairy cow diets up to 30% of the diet DM with no adverse effects on milk yield or milk composition.
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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 | 0.001 | 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) | 0.002 | 0.001 |
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".