Short communication: Genetic parameter estimates for caprine arthritis encephalitis in dairy goats
Bibliographic record
Abstract
Caprine arthritis encephalitis (CAE) is a chronic disease caused by a retrovirus from the Lentivirus genus. No effective vaccines or treatments exist, and therefore genetic selection for CAE resistance might be a feasible alternative. To our best knowledge, no other studies have investigated the genetic architecture of CAE resistance in dairy goats. In this context, this study was designed to estimate genetic parameters for CAE infection in Alpine and Saanen goats using a Bayesian threshold model. A total of 542 adult goats (and >3-generation pedigree), which were group-housed in a population with high CAE prevalence, were tested based on a serological infection assessment test (negative = 1 or positive = 2) and used for this study. Genetic parameters were estimated using the BLUPF90 family programs. There was considerable genetic variability for CAE resistance, and pedigree-based heritability was significantly different from zero (0.026 < heritability < 0.128). Our findings indicate that the prevalence of CAE in goat herds can be reduced or eliminated through direct genetic selection for CAE resistance in addition to proper management strategies.
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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 | 0.003 | 0.017 |
| 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".