Influence of body weight, age, and weight gain on fertility and prolificacy in four breeds of ewe lambs1
Bibliographic record
Abstract
Breeding ewes to lamb at 1 yr of age can improve profitability for some production systems. The first objective of this study was to evaluate the effect of age and weight at breeding and total postweaning weight gain on reproductive performance of ewe lambs. The second objective was to compare the effects of weight and age variables in four major sheep breeds (Columbia, Polypay, Rambouillet, and Targhee). Weights, ages, and the binary traits of fertility (pregnant or nonpregnant) and prolificacy (one lamb born vs. two or more) were collected on 2,055 ewe lambs at the U.S. Sheep Experiment Station, Dubois, ID, from 1984 through 1988. The effects of age and weight at breeding and total weight gain from weaning to breeding on fertility and prolificacy were analyzed with a logit model in a maximum likelihood analyses. Differences (P < 0.001) among breeds for fertility were identified, with a 93% fertility rate for Polypay ewe lambs compared with lower fertility rates in Columbia, Targhee, and Rambouillet ewe lambs (50, 60, and 75%, respectively). The percentage of multiple births (prolificacy rate) also was higher (P < 0.001) in the Polypay (47%) than in Columbia, Targhee, and Rambouillet breeds (1, 13, and 14%, respectively). Averaged across breeds, weight at breeding had a positive effect on fertility and prolificacy (P < 0.001), whereas total weight gain from weaning to breeding had a positive effect only on fertility (P < 0.027). In separate analyses for each breed, increasing age (P < 0.001) and weight at breeding (P < 0.001) increased the probability of pregnancy in Rambouillet ewe lambs. The probability of pregnancy for Targhee ewe lambs increased (P < 0.005) with weight at breeding. Increasing weight at breeding increased (P < 0.004) the probability of multiple births in all breeds. Increasing total postweaning weight gain increased (P < 0.007) the probabilities of multiple births in Rambouillet and Targhee ewe lambs. In conclusion, Polypay ewe lambs were superior in fertility and prolificacy to Columbia, Rambouillet, and Targhee under Western range conditions. Improved reproductive performance of Columbia, Rambouillet, and Targhee ewe lambs may be achieved by increasing age and weight at breeding and postweaning gain.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".