Le déterminisme génétique des myocardiopathies chez les carnivores domestiques
Bibliographic record
Abstract
Cardiomyopathies are myocardial diseases affecting an important number of canine and feline breeds. Their effects in specific predisposed breeds regarding breeding and animal welfare are important. These heart diseases may be clinically very severe, leading to a decrease in life expectancy and quality of life of the animals. Therefore, owners and breeders request tools to get the most accurate diagnosis and the earliest detection of these pathological conditions. The objective of this thesis was to assess the current knowledge regarding the genetic origin of cardiomyopathies in small companion animals, i.e. dilated cardiomyopathy in large breed dogs, arrythmogenic right ventricular cardiomyopathy in Boxers, and hypertrophic cardiomyopathy in cats. The author first presents the genetic basis of techniques to demonstrate the genetic origin of cardiomyopathies. Then, the main genes involved in the heart function in mammals are described, and the genetic origin of cardiomyopathies in humans is specified. In a third part, the author presents the current knowledge on the genetic transmission and origin of cardiomyopathies in different canine and feline breeds and for different types of cardiomyopathies. Those characteristics are described breed by breed (Boxer, Dobermann, Great Dane, Irish wolfhound, Portuguese Water Dog, Newfoundland, Maine Coon, Ragdoll, British Shorthair, Sphynx, American Shorthair, Persian). In a fourth part, the author describes the different tests available to detect the different mutations causing cardiomyopathies in cats and dogs. The author details the usefulness and the limits of those tests when they are used to regulate feline and canine breeding. The breeding strategies to limit the increase in genetic cardiomyopathies are detailed in general, and for each studied breed. Finally, the author presents the reasons why dogs and cats represent an excellent
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".