Analysis of Genetic Diversity of Indian Buffalo Breeds by DNA Markers
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
Buffalo is an important species contributing significantly to Indian economy. There is urgent need to study genetic diversity between and within breeds using appropriate set of microsatellite markers which can be further supplemented by using Genome sequencing data, phonemics and high density arrays. Animal resources are valuable assets of a country. Present buffalo breeds have gene pools of wide representation and valuable combination of genes. Genetic variability also provides the opportunity for tracing the history of populations, species, and their ancestors through DNA based markers. For the overall breed improvement and to meet future challenges there is an urgent need to characterize buffalo breeds. It is our responsibility to conserve, preserve and maintain the animal genetic diversity.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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