Use of SNP genotyping to determine pedigree and breed composition of dairy cattle in Kenya
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
High levels of inbreeding in East African dairy cattle are a potential concern because of use of a limited range of imported germplasm coupled with strong selection, especially by disease, and sparse performance recording. To address this, genetic relationships and breed composition in an admixed population of Kenyan dairy cattle were estimated by means of a 50K SNP scan. Genomic DNA from 3 worldwide Holstein and 20 Kenyan bulls, 71 putative cow-calf pairs, 25 cows from a large ranch and 5 other Kenyan animals were genotyped for 37 238 informative SNPs. Sires were predicted and 89% of putative dam-calf relationships were supported by genotype data. Animals were clustered with the HapMap population using Structure software to assess breed composition. Cows from a large ranch primarily clustered with Holsteins, while animals from smaller farms were generally crosses between Holstein and Guernsey. Coefficients of relatedness were estimated and showed evidence of heavy use of one AI bull. We conclude that little native germplasm exists within the genotyped populations and mostly European ancestry remains.
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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 | 0.000 | 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 | 0.000 |
| 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 it