Effect of development system on growth and reproductive performance of beef heifers1,2
Bibliographic record
Abstract
Reproductive performance was evaluated in beef heifers born over a 2-yr period to determine the effects of target breeding weight (TBW) and development system (SYS) on growth and subsequent reproductive efficiency. Spring-born Angus heifers (253 ± 0.7 kg) were randomly allocated over 2 consecutive yr (yr 1, n = 80; yr 2, n = 96) to be developed to either 55% (350 kg) of mature BW (moderate gain, MG) or 62% (395 kg) of mature BW (high gain, HG). Each MG and HG group was further assigned to 1 of 2 replicated systems: (1) bale graze bromegrass-alfalfa round bales in field paddocks (BG) or (2) fed bromegrass-alfalfa round bales in drylot pens (DL). Heifers were fed a diet of bromegrass-alfalfa hay (56.9% TDN; 9.8% CP) and barley grain supplement (85.1% TDN; 12.3% CP). After the 202-d development period, heifers were exposed to bulls for a 63-d breeding season. Target BW × SYS interactions were not detected for any measured parameters. During the winter development period, MG heifers had lower (P = 0.01) ADG than HG heifers and MG heifers had lighter (P = 0.01) BW at breeding. The proportion of heifers attaining puberty by 14.5 mo of age was less (P = 0.05) in MG (20 ± 4%) than HG heifers (52 ± 3%). From the end of the 202-d development period to pregnancy diagnosis, ADG was greater (P = 0.04) in MG heifers than HG heifers (0.83 vs. 0.71 kg/d). First-calf pregnancy rates were 86 and 88% for MG and HG heifers, respectively (P = 0.41). Second- and third-calf pregnancy rates of cows, developed in either a MG or HG system as heifers, were not different (P = 0.74; 94.7 vs. 95.9% and 93.8 vs. 93.9%, respectively). Economic analysis revealed a $58 reduced development cost for heifers developed to 55% compared with 62% of mature BW without a loss in reproductive performance.
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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 | 0.000 |
| 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) | 0.001 | 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".