Sire Evaluation Based on First Lactation Production Efficiency Traits in Murrah Buffaloes
Bibliographic record
Abstract
The present investigation was undertaken on data of Murrah buffaloes from Buffalo Research Centre (BRC), Chaudhary Charan Singh Haryana Agricultural University, Hisar distributed over 20 years (1987 to 2006). The sire effects and ranks of 38 sires were estimated on the basis of their daughters’ performance. The progeny group size of the sires ranged from 3 to 17. The sires were evaluated for the different first lactation production efficiency traits, viz. first lactation milk yield (FLMY), first lactation peak yield (FPY), persistency of first lactation milk yield (P), average yield per day of lactation (MY/FLL), milk yield per day of first calving interval (MCI) and milk yield per day of age at second calving (MSC). Sire's breeding values were estimated by the best linear unbiased procedure (BLUP). The estimated breeding values (EBV) for FLMY, FPY, P, MY/FLL, MCI and MSC ranged from –288.42 to 362.20 kg; -1.44 to 4.36 kg; -14.72 to 21.09; –0.44 to 0.63 kg/day; -0.40 to 0.52 kg and -0.09 to 0.16 kg, respectively. FLMY had high and significant product-moment and rank correlations with all other traits. The highest product-moment and rank correlations were obtained between FLMY and MSC to the tune of 0.863±0.043 and 0.835±0.050, respectively. The results indicated that sire coding 33 was the best and can be used for future breeding purpose.
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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 | 0.001 |
| 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) | 0.000 | 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".