EFFECTS OF VARYING LEVELS OF DCAD WITH TWO LEVELS OF MG AND K ON ACID BASE STATUS, MG METABOLISM AND PRODUCTIVE PERFORMANCE OF BEETAL GOATS
Bibliographic record
Abstract
Thirty-six Beetal goats in early lactation were used in a 6-wk experiment with a 3 x 2 x 2 factorial arrangement of treatments. The objective was to reveal the effects of three levels of DCAD ( -15, 2.5 and 20mEq/100g of feed DM) with two levels of K (1.35 and 2.0% of feed DM) and two levels of Mg (0. 37 and 0.74%) in diets on productive performance. Increasing DCAD levels in diets significantly increased DMI, milk yield and milk fat percentage. Moreover, increasing K levels in diets increased milk yield of goats. However, increasing Mg levels in diets from 0.37% to 0.74% of feed DM negatively influenced the DMI intake, DM digestibility, milk yield and milk protein contents, as all the traits were reduced by increasing Mg levels. A linear increase in pH and HCO 3 − contents of blood and urine by increasing DCAD levels in diets evidenced a positive alteration in acid base status of the animals. However, K and Mg l evels of diets showed no effect on same traits. Moreover, increasing K levels of diets reduced the Mg absorption. Similarly, higher Mg absorption, retention and balance were observed when added Mg was increased in diets. Overall, increasing DCAD levels in diets improved DMI and milk yield (3.5 and 11.1%, respectively), however, increasing Mg levels in diets showed negative effects on productive performance of Beetal goats.
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How this classification was reachedexpand
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 teacher head, 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".