Comparison of Holstein bull semen sources on milk traits in Isfahan province in Iran
Bibliographic record
Abstract
Abstract. This research provides a comparison of productivity of daughters in Iran sired by bulls from Canada, Europe, Iran, and the United States. Data were collected by the Animal Breeding Center of Iran on pedigree and first lactation performances of 10,192 Holsteins sired by 186 imported (including: 39 European, 73 American, 74 Canadian) and 133 Iranian bulls, which had their first calving in 35 dairy herds in Isfahan province. The results showed that American and European daughters had the highest performances for milk yield. The highest mean for fat yield was related to European daughters. American sires on average had the highest genetic potential for yield traits; however, they had the lowest fat percentage among compared sire groups. Canadian sire group was intermediate relative to American, European and Iranian groups. Higher intercepts and regression coefficients of conversion equations for American sires showed that more returns will be achieved from one genetic point superiority of American sires relative to Canadian sires in the environments of Isfahan province. The Iranian sire group had the lowest predicted transmitting ability means for both milk and fat yields and a negative predicted transmitting ability mean for fat percentage. This study showed that due to low to intermediate predicted transmitting ability correlations between foreign evaluations and the evaluations made by this study, direct selection based on foreign national evaluations would not lead to optimal results for the traits concerned. So, the genetic potential/expression of imported genetic materials needs to be reevaluated by the Animal Breeding Centers of Iran.
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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 | 0.001 | 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) | 0.001 | 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".