Phenotypic and genotypic characterization of lumbosacral stenosis in Labrador retrievers
Bibliographic record
Abstract
Lumbosacral stenosis (LS) is a structural narrowing of the spinal canal in the canine lumbosacral spine. Large-sized working and sporting dog breeds such as Labrador retrievers are predisposed for reasons that are incompletely understood. Early diagnosis is essential for maximizing the quality of life, and minimizing the likelihood of early retirement in working dogs. Lumbosacral stenosis is usually considered to be a condition associated with degenerative changes observed with normal aging, however presence of the disease in young and middle aged working dogs has also been reported. This leads to the probable theory that some dogs in large breeds like Labrador retrievers might be genetically pre-disposed to LS.;Radiographic screening is common practice for agencies that purchase, train, and use working dogs. Dogs with morphologic traits such as canine hip dysplasia, canine elbow dysplasia, and transitional lumbosacral vertebrae are commonly rejected. However radiographs are insensitive for detecting LS. Advanced imaging methods such as computed tomography (CT) and magnetic resonance imaging (MRI) and the current standard diagnostic tests for detection of LS. These modalities are considered to be complimentary, with each offering different strengths for visualization of bony and soft tissue structures. For working dogs, computed tomography offers advantages of greater availability and the faster scanning times that allow the use of reversible sedation. Qualitative CT phenotyping is a standard method for clinical diagnosis of LS in dogs. However, for research purposes, a method for quantitative phenotyping of LS would also be beneficial. There is a lack of published evidence for a consensus on any such quantitative CT phenotypic traits in humans or dogs. In the first study, we developed one such quantitative trait using CT imaging in a sample of 25 Labrador retrievers---fat area ratio or FAR (ratio of the vertebral canal fat area content in a transverse slice to the vertebral body area in the same transverse slice). This measurement was found to have good agreement with the standard qualitative assessment of LS (as made by a certified veterinary radiologist); and we propose that FAR can be used to quantify LS especially in a research capacity.;Lumbar spinal stenosis (LSS) is a human condition that is often considered to be orthologous to canine LS. Genetic studies in humans have shown promise in identification of possible genetic factors that might be associated with LSS. The predominant genetic approach for research in canine LS has been pedigree analysis especially in the German shepherds;
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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 | 0.000 | 0.000 |
| 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) | 0.001 | 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".