Improved quality of Kambing Kacang sexing frozen semen with the addition of green tea extract
Bibliographic record
Abstract
Objective: The objective of this study was to determine the effect of adding various doses of green tea extract to the semen of Kacang goats during the sexing process on motility, viability, membrane integrity, malondialdehide (MDA), and deoxyribonucleic acid (DNA) fragmentation. Materials and Methods: It started with the containment of the semen of the Kacang goat, followed by macroscopic and microscopic examinations. If the semen was considered viable, a diluter that had been added with various doses of green tea extract would be added to the semen. After that, sexing was carried out using the percoll gradient density medium. Next, the sexed semen was cryopreserved in liquid nitrogen. Then, an examination of motility, viability, membrane integrity, MDA, and DNA fragmentation was conducted. Result: . Conclusion: The addition of green tea extract can improve the quality of the sexed semen of the Kacang goat after it has been cryopreserved.
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How this classification was reachedexpand
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 | 0.002 | 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 | 0.001 |
| 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 teacher head, 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".