Assessment of collagen genes involved in fragmented medial coronoid process development in Labrador Retrievers as determined by affected sibling-pair analysis
Bibliographic record
Abstract
OBJECTIVE: To evaluate the involvement of various collagen genes in the development of fragmented medial coronoid process (FCP) in Labrador Retrievers. SAMPLE POPULATION: 93 dogs originating from 13 litters were used in the study; FCP was diagnosed in 35 dogs, and each affected dog had at least 1 sibling that was also affected. Twelve dams and sires were included in the analysis. All dogs were purebred Labrador Retrievers except for 2 litters (offspring of a female Golden Retriever-Labrador Retriever mixed-breed dog). PROCEDURES: For each dog, DNA was isolated from blood samples. Polymorphic microsatellite markers adjacent to 14 candidate genes (ie, COL1A1, COL1A2, COL2A1, COL3A1, COL5A1, COL5A2, COL6A3, COL9A1, COL9A2, COL9A3, COL10A1, COL11A1, COL11A2, and COL24A1) were analyzed by use of PCR assays; genotypes were determined via automated detection of DNA products. The level of allele sharing between pairs of affected siblings was assessed. RESULTS: Among the 93 dogs, allele sharing of the 14 collagen genes was determined as follows: COL1A1, 45%; COL1A2, 47%; COL2A1, 37%; COL3A1, 32%; COL5A1, 43%; COL5A2, 32%; COL6A3, 36%; COL9A1, 45%; COL9A2, 49%; COL9A3, 38%; COL10A1, 46%; COL11A1, 52%; COL11A2, 47%; and COL24A1, 47%. CONCLUSIONS AND CLINICAL RELEVANCE: Because siblings share 50% of their genome at random, the fact that the percentages of allele sharing among the analyzed collagen genes were not significantly > 50% indicates that these genes are not determinant candidates for FCP in Labrador Retrievers. The gene for the vitamin D receptor could also be excluded because of its proximity to COL2A1.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".