Emerging insights into the genetic basis of canine hip dysplasia
Bibliographic record
Abstract
Canine hip dysplasia (CHD) is the most common inherited polygenic orthopedic trait in dogs with the phenotype influenced also by environmental factors. This trait was described in the dog in 1935 and leads to a debilitating secondary hip osteoarthritis. The diagnosis is confirmed radiographically by evaluating signs of degenerative joint disease, incongruence, and/or passive hip joint laxity. There is no ideal medical or surgical treatment so prevention based on controlled breeding is the optimal approach. The definitive CHD diagnosis based on radiographic examination involves the exposure to ionizing radiation under general anesthesia or heavy sedation but the image does not reveal the underlying genetic quality of the dog. Phenotypic expression of CHD is modified by environmental factors and dogs with a normal phenotype can be carriers of some mutations and transmit these genes to their offspring. Programs based on selection of dogs with better individual phenotypes for breeding are effective when strictly applied but remain inferior to the selection of dogs based on estimation of breeding values. Molecular studies for dissecting the genetic basis of CHD are ongoing, but progress has been slow. In the future, the recommended method to improve hip quality in controlled breeding schemes, which will allow higher selection pressure, would be based on the estimation of the genomic breeding value. Since 2012, a commercial DNA test has been available for Labrador Retrievers using a blood sample and provides a probability for development of CHD but we await evidence that this test reduces the incidence or severity of CHD.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".