Effect of types of breeding on embryo survival following first AI in lactating Holstein cows
Bibliographic record
Abstract
The main objective was to investigate the effects of timed-AI protocols versus AI following oestrus detection on circulating progesterone (P4) and embryo survival after first service in Holstein cows. Cycling status was determined by ultrasonography and by plasma P4 concentrations 14 and 26 days after calving, and only cows with a corpus luteum and/or P4 ≥ 1 ng/ml were used. Cows were randomly allocated to one of three types of breeding: DO (n = 80), received GnRH-7d-PGF2α-3d-GnRH and Ovsynch56 was initiated 7 days later; G7G (n = 70), received PGF2α-2d-GnRH and Ovsynch56 (GnRH-7d-PGF2α-56h-GnRH-16h-AI) was initiated 7 days later; or AI based on oestrus detection, EDAI (n = 60). Progesterone was also determined at AI and 8, 16, 18 and 20 days after AI; ISG15 and MX2 mRNA abundance were determined 16 days after AI. Mean plasma P4 at AI was greater in the EDAI group compared with DO and G7G groups, while after AI, P4 was greater in DO and G7G groups compared with EDAI group. However, the percentage of cows with a concentration of P4 < 0.8 ng/ml at AI did not differ among groups. Relative mRNA abundance of ISG15 and MX2 was greater in the DO and G7G groups compared to those in EDAI group. Pregnancy per AI 16, 32 and 60 days after AI was greater (p < .05) in cows in the DO group compared with those in EDAI group (47.5%, 38.8% and 36.3% vs. 30.0%, 21.7% and 15.0%). Pregnancy losses between 16 and 60 days after AI were greater (p < .05) in cows in the EDAI (50.0%) group compared to those subjected to DO (23.7%) or G7G (24.1%). In conclusion, the use of timed-AI synchronization protocols resulted in greater circulating P4 concentrations post-AI and greater embryo survival following first service in lactating Holstein cows.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".