Modifications of the G6G timed-AI protocol improved pregnancy per AI and reduced pregnancy loss in lactating dairy cows
Bibliographic record
Abstract
In dairy cows, subjected to a G6G protocol, objectives were to determine effects of (1) extending the interval from prostaglandin F2α (PGF2α) to gonadotropin-releasing hormone (GnRH) during presynchronization; and (2) adding a second PGF2α treatment before artificial insemination (AI), on ovarian response, plasma progesterone (P4) concentrations and pregnancy per AI (P/AI). In a 2×2 factorial design, lactating cows were randomly assigned to one of four timed AI (TAI) protocols: (1) G6G (n=149), one injection of PGF2α, GnRH 2 days later and a 7-day Ovsynch (GnRH, 7 days, PGF2α, 56 h, GnRH, 16 h, TAI) was initiated 6 days later; (2) G6GP (n=144), an additional PGF2α treatment (24 h after the first) during Ovsynch of the G6G protocol; (3) MG6G, one injection of PGF2α, GnRH 4 days later before initiation of the G6G protocol; and (4) MG6GP, an additional PGF2α treatment (24 h after the first) during Ovsynch of the MG6G protocol. Blood samples were collected (subset of 200 cows) at first GnRH and PGF2α of the Ovsynch, and at TAI to measure P4. Ultrasound examinations were performed in a subset of 406 cows to evaluate ovarian response at various times of Ovsynch, and in all cattle to determine pregnancy status at 32 and 60 days after TAI. Extending the interval by 2 days between PGF2α and GnRH during presynchronization increased (P<0.01) ovulatory response to first GnRH of Ovsynch, circulating P4 during Ovsynch, and P/AI at 32 and 60 days after TAI. Adding a second PGF2α treatment before AI increased the proportion of cows with luteal regression (P=0.04), improved P/AI at 60 days after TAI (P=0.05), and reduced pregnancy loss between 30 and 60 days after TAI (P=0.04). In summary, extending the interval from PGF2α to GnRH during presynchronization increased response to first GnRH of Ovsynch and P4 concentrations during Ovsynch, whereas adding a second PGF2α treatment before AI enhanced luteal regression. Both modifications of the G6G protocol improved fertility in lactating dairy 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 | 0.000 | 0.000 |
| 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".