SNP‐based heritability and genetic architecture of cranial cruciate ligament rupture in Labrador Retrievers
Bibliographic record
Abstract
Cranial cruciate ligament rupture (CCLR) is one of the leading causes of pelvic limb lameness in dogs. About 6% of Labrador Retrievers suffer from this orthopedic problem. The aim of this study was to determine the heritability of CCLR in this breed using SNP array genotyping data. DNA samples were collected from CCLR-affected dogs (n = 190) and unaffected dogs over the age of 8 years (n = 143). All 333 dogs were genotyped directly or imputed up to approximately 710k SNPs on the Affymetrix Axiom CanineHD SNP array. Heritability of CCLR was calculated using multiple methodologies, including linear mixed models, Bayesian models and a model that incorporates LD. The covariates of sex and sterilization status were added to each analysis to assess their impact. Across the algorithms of these models, heritability ranged from 0.550 to 0.886, depending on covariate inclusion. The relatively high heritability for this disease indicates that a substantial genetic component contributes to CCLR in the Labrador Retriever.
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.
How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".