Estimation of Phenotypic and Genetic Parameters and Genetic Trend of Weights in the Weaning Phase (P205), Weight at one Year (P365), the Yearling (P505) in Nellore Cattle in the Northern Region and Under-Region Middle-North of Brazil
Bibliographic record
Abstract
We studied 257 herds of 257 farms, totaling 79,051 observations in eight States of the Federation, which genetic and phenotypic parameters were estimated for the weights to 205 (P205), 365 (P365) and 550 days old (P550) of Nelore, included in the system of development Control by weight (CDP) conducted by the Brazilian Association of Zebu breeders (ABCZ) and raised in the northern region and sub-region Means North. Estimates of variance components and genetic parameters were obtained by the MTDFREML application, which uses the methodology of the Restricted Maximum Likelihood Derivative Free with an animal model that considers as fixed the effects of the farm such as year, month of birth, and gender. The heredity for P205 was 0.13 ± 0.02 and for P365 was 0.18 ± 0.05, which may indicate little additional genetic variation for these characteristics. For P550 days the estimated heredity was 0.23 ± 0.07, considered average, what indicates that at this age it is possible to select for weight gain. The genetic, phenotypical and environmental likeness among the weights in different ages were: P205-P365 = 0.92, 0.72 and 0.79; P205-P550 = 0.89, 0.61 and 0.87 and P365-550 = 0.98, 0.80 and 0.87. The genetic tendency in P365, for direct effect was significant and positive equals 0.455 kg (P < 0.001). Genetic trends in P205, P365 and P550 for direct effect were significant and positive, equal to 0.272 kg (P < 0.001), 0.455 kg (P < 0.001) and 0.744 kg (P < 0.001), respectively.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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".