An International Genetic Survey of Breed-Specific Diseases in Working Dogs from the United States, Israel, and Poland
Bibliographic record
Abstract
Genetic diseases occur in breeds used for law enforcement. As important team members, dogs are expected to operate at peak performance for several years and are significant investments for both the initial purchase and extensive, specialized training. Previous studies have not focused on causes for retirement or euthanasia as genetic (inherited) versus acquired (environmental). We performed direct mutational analysis for breed-specific conditions on samples from 304 dogs including 267 law enforcement (122 US, 87 Israeli, and 58 Polish) and 37 search and rescue dogs. Genetic testing identified 29% (n = 89) of the dogs tested to be carriers of a genetic mutation and 6% (n = 19) to be at risk for a debilitating inherited condition that may eventually impair the dog's ability to work. At-risk dogs included Labrador Retrievers (n = 4) with exercise-induced collapse, Bloodhounds (n = 2) with degenerative myelopathy (DM), and German Shepherd dogs with DM (n = 12) or leukocyte adhesion deficiency, type III (n = 1). A substantial number of working dogs were shown to be at risk for genetic conditions that may shorten the dog's career. The loss of dogs, due to early retirement or euthanasia, as a result of preventable genetic conditions has an emotional cost to handlers and financial cost to service organizations that can be avoided with genetic screening prior to breeding, buying, or training.
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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 | 0.000 | 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 | 0.001 |
| 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".