Effects of vitamins and trace-elements supplementation on milk production in dairy cows: A review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
During the past decade, significant advances were made in understanding the effects of vitamins and trace-elements supplement on milk production of dairy cows. This work discussed the effects of vitamins and trace-elements supplementation on milk production of dairy cows. Studies have indicated that vitamin A (VA) and β-carotene (BC) supplementation have some effects on udder health and milk yield in dairy cows whose intake is below 110 IU/kg BW/day. If low quality forage is fed, supplementation of VA should be considered. Supplementation of B-vitamin has important effects on milk production and could increase milk yield and milk component production. The effect of vitamin E (VE) and selenium (Se) supplementation on the milk yield and milk components are not unified due to the optimum dose, route and timing of VE administration in lactational dairy cows. Zinc (Zn) supplementation increases lactation performance and reduces milk somatic cell count (SCC) in most studies. Limited research has indicated that copper (Cu) supplementation could reduce milk SCC. Before deciding to supplement vitamins and trace-minerals indicated earlier for the improvement of milk production of lactational cows, farmers should have their animals fed with tested and evaluated rations to be sure of the levels of supplementation which may be warranted. Key words: Vitamin, trace-element, dairy cow, milk production.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it