Short Communication: Pregnancy Rates to Timed Artificial Insemination in Holstein Heifers Given Prostaglandin F2α Twenty-Four Hours Before or Concurrent with Removal of an Intravaginal Progesterone-Releasing Insert
Bibliographic record
Abstract
The objective was to compare pregnancy rates in nulliparous Holstein heifers given PGF(2alpha) 24 h before, or concurrent with, removal of an intravaginal progesterone-releasing (CIDR) insert in 3 timed artificial insemination (TAI) protocols. Heifers (from 2 herds) were assigned randomly, over 11 mo, to 1 of 3 modified Ovsynch protocols. On d 0 (without reference to the stage of the estrous cycle), all heifers were given 100 microg of GnRH i.m. and a CIDR insert (containing 1.9 g of progesterone). In the PG-7/P4-8 protocol (n = 99), PGF(2alpha) was given on d 7, and CIDR inserts were removed on d 8. In the PG-7/P4-7 (n = 98) and PG-8/P4-8 (n = 102) protocols, PGF(2alpha) administration and CIDR removal occurred concurrently, on d 7 or 8, respectively. In all 3 protocols, a second GnRH treatment (100 microg) was given 48 h after PGF(2alpha) with TAI 16 to 20 h later. Blood samples were collected (subset of 124 heifers) on d 0, 7, 10 or 11 (i.e., at TAI), and 17. Pregnancy rates (32 d after TAI) for protocols PG-7/P4-8, PG-7/P4-7, and PG-8/P4-8 were 61.8, 55.6, and 54.1%, respectively. Pregnancy rate was higher when synchronization was initiated during diestrus than when initiated at other stages (57.0 versus 34.8%). Although pregnancy rates were not affected by season, there was an interaction between protocol and season; pregnancy rates were significantly lower in summer in heifers subjected to PG-7/P4-7 and PG-8/P4-8, but season did not affect pregnancy rates in heifers subjected to PG-7/P4-8. In summary, giving PGF(2alpha) 24 h before CIDR removal, followed by TAI (PG-7/P4-8 protocol), resulted in consistent pregnancy rates, regardless of season, relative to protocols involving PGF(2alpha) treatment concurrent with CIDR removal.
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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".