Application of PGF2α at the moment of fixed-time artificial insemination in crossbred beef cows
Bibliographic record
Abstract
Although studies have shown positive effects of gonadotropin releasing hormone (GnRH) or prostaglandin F2α (PGF2α) at the moment of fixed-time artificial insemination (FTAI) in the conception rate (CR) of cattle, its effects on treatments based on progesterone (P4) and estradiol benzoate (EB) is still not conclusive. The objective of this study was (1) to evaluate the effect of a PGF2α analogue at FTAI in the CR of crossbred beef cows submitted to a 11d FTAI protocol based on P4 and EB; and (2) to describe the CR between PGF2α-treated and control cows in different body condition scores (BCS) and parity categories. Crossbred (½ Nellore and ½ Angus) beef cows were submitted to a synchronization protocol and randomly assigned into 2 groups: Control (n = 163), at FTAI cows received 2 mL of saline solution as a placebo, and PGF2α (n = 163), at FTAI cows were treated with PGF2α analogue (10 mg of dinoprost tromethamine). Pregnancy diagnosis was performed 33d post-FTAI. Binary logistic regression model was used to analyze the effect of PGF2α treatment on CR. There was no difference in CR between PGF2α and control groups (P > 0.05; odds ratio (OR) = 0.92; confidence interval (CI) = 0.59-1.4). A greater CR was found in heifers (P = 0.0006, OR = 2.65, CI = 1.61 - 4.38) and multiparous (P = 0.0006, OR = 2.12, CI = 1.04 - 4.3) when compared to primiparous cows. Cows with low BCS (4; 9-point scale) showed lower CR when compared with moderate BCS (5-6; 9-point scale) (P < 0.05; OR = 0.10; CI = 0.06 - 0.18). There was no numerical difference on CR between PGF2α-treated and control cows in different BCS and parity categories. The results suggested that the CR in this study was not influenced by 10 mg PGF2α analogue at FTAI.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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) | 0.000 | 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 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".