Power of a Labrador Retriever-Greyhound pedigree for linkage analysis of hip dysplasia and osteoarthritis
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVE: To estimate the number of dogs required to find linkage to heritable traits of hip dysplasia in dogs from an experimental pedigree. ANIMALS: 147 Labrador Retrievers, Greyhounds, and their crossbreed offspring. PROCEDURE: Labrador Retrievers with hip dysplasia were crossed with unaffected Greyhounds. Age at detection of femoral capital ossification, distraction index (DI), hip joint dorsolateral subluxation (DLS) score, and hip joint osteoarthritis (OA) were recorded. Power to find linkage of a single marker to a quantitative trait locus (QTL) controlling 100% of the variation in a dysplastic trait in the backcross dogs was determined. RESULTS: For the DI at the observed effect size, recombination fraction of 0.05, and heterozygosity of 0.75, 35 dogs in the backcross of the F1 to the Greyhound generation would yield linkage at a power of 0.8. For the DLS score, 35 dogs in the backcross to the Labrador Retriever generation would be required for linkage at the same power. For OSS, 45 dogs in the backcross to the founding Labrador Retrievers would yield linkage at the same power. Fewer dogs were projected to be necessary to find linkage to hip OA. Testing for linkage to the DLS at 4 loci simultaneously, each controlling 25% of the phenotypic variation, yielded an overall power of 0.7 CONCLUSIONS AND CLINICAL SIGNIFICANCE: Based on this conservative single-marker estimate, this pedigree has the requisite power to find microsatellites linked to susceptibility loci for hip dysplasia and hip OA by breeding a reasonable number of backcross dogs.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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