Development of in vitro tests to predict fertility of bulls
Bibliographic record
Abstract
The overall objective was to develop an in vitro test to predict fertility of bulls in the field. We investigated the bull effect on in vitro embryo production, zona binding and acrosome reaction, and the correlation of this effect to field fertility meas ured by 60–90 d non-return rate. Frozen semen from three separate ejaculates of eight unrelated young bulls, obtained from an artificial insemination (AI) center, was used. On thawing, ejaculates from each bull were pooled, motile sperm were selected and (a) subjected to immunofluorescent assay at 0 and 4 h of incubation in capacitation medium to assess acrosome status, (b) used in an in vitro fertilization assay system to assess cleavage and blastocyst production rates, and (c) sperm-zona binding assay was carried out to determine the number of sperm bound to the zona pellucida of mature oocytes. Percentage of pre-freeze motile sperm (PrFM) and non-return rate data were obtained from the AI center. PrFM, percentage of acrosome reacted sperm at 0 h (AR1), increase in percentage of acrosome reacted sperm after 4 h (InAR) and sperm-zona binding rates (ZB) differed (P < 0.05) among sperm samples obtained from different young bulls. Significant correlations (P < 0.05) were observed between PrFM and AR1 (r = -0.31), InAR (r = 0.36), and ZB (r = 0.32). AR1 was negatively correlated to ZB (r = -0.27) and cleavage rate (r = -0.20), InAR was positively correlated with ZB (r = 0.31) and cleavage rate (r = 0.26). None of the in vitro tests was correlated with non-return rate. These findings indicate that along with pre-freeze motility, a combination of in vitro tests including the percentage of spontaneously acrosome reacted sperm at thawing, might be useful in predicting bull field fertility. Such a combination of assays, however, has yet to be determined. Key words: Field fertility, acrosome reaction, zona binding, IVF, fertility assay
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".