Survival analysis and reproductive performance of Dorper x Tumele sheep
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Productivity and profitability of sheep farming are highly influenced by lamb survival and ewe reproductive performance. Thus, this study was conducted to evaluate the survival and reproductive performance of crossbred sheep. Data collected from 2009 to 2018 from Sirinka sheep breeding stations were utilized for this study. Survival analysis was conducted by using Survival Kit 6.12 software with the Weibull model and the general linear model of SAS 9.0 was used to analyze reproductive traits. The overall mean survival rate of Dorper x Tumele crossbred lambs at 3, 6 and 12 months of age were 86.0, 76.6, and 67.9%, respectively. About 46.8% of mortality from the total death was observed during the first 120 days of life. Gastrointestinal parasites, pneumonia and septicemia were the major causes of lamb mortality. Birth weight, birth type, sex and year of lambing were the most important risk factors for survival of crossbred lambs. The overall least-squares means for litter size at birth, litter size at weaning, total litter weight at birth and total litter weight at weaning were 1.10 lambs, 0.94 lambs, 3.28 kg and 15.5 kg, respectively. Birth type, sex and year of lambing were the most determinants of ewe productive traits. Tumele and their crossbred sheep had good mothering ability necessary to successfully raise lambs to weaning. The current crossbreeding program which aims to improving growth performance had a positive influence on the survival rate of lambs. Improvement of environmental in the flock, special care for small lambs and indirect selection based on birth weight would lead to further survival improvement.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it