Effect of Initial Gn<scp>RH</scp> and Duration of Progesterone Insert Treatment on the Fertility of Lactating Dairy Cows
Bibliographic record
Abstract
The study compared response to prostaglandin F2α (PG), synchrony of ovulation and pregnancy per AI (P/AI) in a 5- vs a 7-day Ovsynch + PRID protocol and investigated whether the initial GnRH affects P/AI in lactating dairy cows. Two hundred and seventy-six cows (500 inseminations) were assigned to one of four timed-AI (TAI) protocols: (i) PRID-7G; 100 μg GnRH im, and a progesterone-releasing intravaginal device (PRID) for 7 days. At PRID removal, PG (500 μg of cloprostenol) was given im. Cows received the second GnRH treatment at 60 h after PRID removal and TAI 12 h later. (ii) PRID-5G; as PRID-7G except the duration of PRID, treatment was 5 days and PG was given twice (12 h apart). (iii) PRID-7NoG; as PRID-7G except the initial GnRH, treatment was omitted. (iv) PRID-5NoG; as PRID-7NoG except the duration of PRID, treatment was 5 days. Response to treatments and pregnancy status at 32 and 60 days after TAI was determined by ultrasonography. The percentage of cows ovulating before TAI was greatest in PRID-7G (17.1%), and the percentage of cows that did not have luteal regression was greatest in PRID-5G (9.5%). The overall P/AI at 32 and 60 days did not differ among TAI protocols. However, during resynchronization, cows subjected to the 5-day protocols had greater (p < 0.05) P/AI (45.3% vs 33.6%) than cows subjected to the 7-day protocols. Pregnancy loss between 32 and 60 days tended (p = 0.10) to be greater in cows that did not receive initial GnRH (14.8%) compared to those that received GnRH (8.2%). In conclusion, the PRID-5G protocol resulted in fewer cows responding to PG, but P/AI did not differ among TAI protocols. A 5-day protocol resulted in more P/AI in resynchronized cows, and cows that did not receive initial GnRH tended to experience more pregnancy losses.
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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 | 0.001 |
| 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) | 0.001 | 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".