Evaluation of dehydrated corn silage as the primary forage for lactating dairy cows
Bibliographic record
Abstract
The objective was to compare productivity of lactating dairy cows fed dehydrated corn silage with those fed whole-crop barley silage. Twelve multiparous Holstein cows in mid lactation were fed diets containing dehydrated corn silage (DCS) or barley silage with additional grain (BSHG) or without (BSLG) in a 3 × 3 Latin square design, with 21-d periods, balanced for carryover effects. The dietary starch content was similar for DCS and BSHG diets, and dietary forage content was similar for DCS and BSLG diets. Experimental diets did not affect dry matter intake, but cows fed DCS diet decreased milk yield compared with those fed barley silage regardless of the dietary starch content. Apparent total-tract digestibility of starch and crude protein was also lower for cows fed DCS compared with those fed barley silage, and milk urea N content was lowest for cows fed DCS diet, indicating that DCS likely had less protein degradation in the rumen than barley silage. Milk fat content and yield, energy-corrected milk yield, and feed efficiency were not different between cows fed BSHG and DCS diets, but higher for cows fed BSLG than those fed BSHG or DCS diet, which can be attributed to the difference in dietary starch content. Feeding DCS in place of barley silage did not improve productivity of lactating dairy cows in the current study, and further research is warranted to optimize its utilization in dairy diets.
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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".