Comparison of FTAI and Natural Service Breeding Programs on Beef Cow Reproductive Performance, Program Cost and Partial Budget Evaluation
Bibliographic record
Abstract
The study compared a natural-service breeding (NSB) program to a single fixed-time artificial insemination (FTAI) program on beef cow reproductive efficiency, breeding costs and partial budget evaluation. Eighty Black Angus lactating beef cows (5-6 yrs of age; n = 80; BW = 599.4±78.6 kg) were randomly assigned by age, days postpartum to either FTAI (FTAI cow) or NSB (NSB cow) breeding program. The FTAI cows received a CIDR for 7 d and 100 μg (2 mL) i.m. injection of GnRH, following this 25 mg (5 mL) i.m. of PGF2α i.m. with CIDR removed. Then a second 25 mg (5 mL) i.m. injection of GnRH approximately 66 h (d 10) after initial injection to ensure luteal regression, and artificially inseminated with semen by a trained technician. The NSB cows were exposed to bulls at a bull:cow ratio of 1:25 for a 63 d breeding season. Results indicated that a NSB program can be a lower cost ($85 vs. $123) compared to FTAI program on a per cow basis. If improvements in conception rate, calf weaning rate, and total 205 d adjusted wean weights are incorporated, a partial budget analysis reveals FTAI can increase net profit by $284 per cow.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".