Optimization of BSA Column Gradient Concentrations on Post-Thaw Quality of Sexed Spermatozoa in Bali Bulls
Bibliographic record
Abstract
This study evaluated post-thaw semen quality and the proportions of X- and Y bearing spermatozoa in Bali cattle semen sexed by albumin of bovine serum albumin (BSA) column using two different gradients. In this study, frozen semen from a Bali bull was used, with three treatments: T0 (non-sexed frozen semen as a control), T1 (BSA 5%:8%), and T2 (BSA 5%:10%). The parameters observed were individual motility, viability, abnormality, concentration, total motile sperm (TSM), and sperm proportion. The results showed that sperm motility in the upper fraction (UF) was highest under T2 (41.57%), whereas in the lower fraction (LF) it peaked under T1 (24.15%). Sperm viability was highest in the UF under T1 (57.69%) and in the LF under T1 (39.02%). The lowest abnormality was observed in the UF under T2 (4.64%) and in the LF under T1 (7.27%). Sperm concentration reached 30.14 million/straw in the UF under T2 and 22.27 million/straw in the LF under T2. Total sperm motility (TSM) was highest in the UF under T2 (12.57 million/straw) and in the LF under P1 (4.76 million/straw). The sperm proportions of the UF reached 75% X (T1) and the LF 81.71% Y (T1). Overall, the upper fraction obtained from the 5%:8% BSA gradient provided acceptable post-thaw sperm quality and adequate X/Y sperm enrichment, supporting its suitability for artificial insemination.
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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 | 0.000 | 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 | 0.001 | 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 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".