Progressive motility – a potential predictive parameter for semen fertilization capacity in bovines
Bibliographic record
Abstract
We examined the association between progressive motility of spermatozoa and in vitro fertilization (IVF) competence of bovine ejaculates. Fresh semen was evaluated using a computerized sperm quality analyzer for bulls using progressive motility as the primary parameter. Ejaculates with high progressive motility (HPM; >81%) were compared with those with low progressive motility (LPM; 0.05). Examination of sperm morphology revealed a higher proportion of spermatozoa with abnormal morphology (P < 0.01) in LPM versus HPM ejaculates, the predominant abnormal feature being a bent tail (P < 0.05). Sperm viability, acrosome integrity and DNA fragmentation did not differ between HPM and LPM samples. Mitochondrial membrane potential was higher (P < 0.01) in HPM versus LPM semen. Zinc concentrations in the seminal plasma correlated with progressive motility (R2 = 0.463, P = 0.03). In addition, representative ejaculates from HPM and LPM groups were cryopreserved in straws and used for IVF. The proportions of embryos cleaved to 2- and 4-cell stages (88.1 ± 1.1 versus 80.5 ± 1.7, P = 0.001) and developed to blastocysts (33.5 ± 1.6 versus 23.5 ± 2.2, P = 0.026) were higher for HPM than LPM semen. The total cell number of embryos and blastocyst apoptotic index did not differ between groups. Although sperm progressive motility is associated with IVF competence, further examination is required to determine whether progressive motility can serve as a predictor of semen fertilization capacity in vivo.
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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 | 0.000 | 0.001 |
| 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 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".