The effect of thawing temperature and duration on the quality of frozen semen of horned and polled Bali cattle
Bibliographic record
Abstract
This research aimed to determine the effect of different thawing temperatures and durations on horned and polled Bali cattle with temperatures of 34°C, 37°C, and 40°C with a duration of 20, 30, and 35 seconds to obtain the quality of frozen semen of horned and polled Bali cattle optimally. This research used horned and polled Bali cattle from the Center of Artificial Insemination in South Sulawesi, Indonesia, after the semen was collected and packaged in frozen semen, motility and viability were observed at the In-Vitro Embryo Production Laboratory, Hasanuddin University. The research method used was an experimental method using a Completely Randomized Design with three replications of treatment for each frozen semen of horned and polled Bali cattle. The results showed that the treatment of horned and polled Bali cattle with thawing temperatures of 34°C, 37°C, and 40°C with a duration of 20, 30, and 35 seconds did not have a significant difference on motility. The viability of horned Bali cattle with thawing temperatures of 34°C, 37°C, and 40°C did not have a significant difference, but with thawing duration of 20, 30 and 35 seconds gave a significant difference. Meanwhile, in polled Bali cattle, the thawing temperature and duration of 34°C, 37°C, and 40°C with the duration of 20, 30, and 35 seconds had a significant difference on viability. Based on this research, it can be concluded that the motility of horned and polled Bali cattle by thawing at temperatures of 34°C, 37°C, and 40°C with the duration of 20, 30 and 35 seconds can be used. In the viability of horned Bali cattle, it was concluded that thawing at 37°C with the duration of 30 seconds gave the best quality spermatozoa, while polled Bali cattle concluded that thawing at 37°C with the duration of 20 seconds gave the best quality of spermatozoa as well.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".