Análisis de la diversidad genética de la población de Toros Jersey y Brown Swiss importados al Ecuador entre los años 2000-2021.
Bibliographic record
Abstract
Genetic diversity is important for the survival of species, favoring evolutionary processes. The research aimed to evaluate the genetic diversity of the population of Jersey and Brown Swiss bulls imported to Ecuador between the years 2000-2021 through their genealogical information for which an analysis of consanguinity coefficient was carried out, the genetic relationships between bulls imported and currently marketed in Ecuador. From digital and physical catalogs of the bovine semen marketing companies, 67 Jersey bulls and 58 available Brown Swiss bulls were determined, imported between 2000-2021. For the analysis of the flow and genetic relationships, information corresponding to name, international code, country, date of birth of the imported bull and its paternal and maternal ancestors, queries in the databases of the countries of origin of the ancestors, in 4 generations or more, were used. The value of the percentile, consanguinity by pedigree and genomics was evaluated. The statistical analysis was processed in INFOSTAT. The coefficient of consanguinity and the average kinship with the ENDOG v4.8 program. Jersey genetics from the United States and Canada are responsible for 94% and 4% respectively of gene flow to Ecuador, unlike Brown Swiss genetics from the United States 63% and Switzerland 11% is responsible for gene flow to Ecuador. The average age of Jersey bulls evaluated was 12.63 years and Brown Swiss bulls was 7.99 years. Regarding the consanguinity there is a percentage index 7.75% of the Jersey race and 1.12% of the Brown Swiss breed.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".