Prevalence of Cardiac Disorders in Canines-A Clinical Study
Bibliographic record
Abstract
The aimed study was to evaluate the prevalence of cardiac disorders in canines based on clinical presentation, laboratory, electrocardiographic, radiographic, two dimensional echocardiography, M-mode echocardiography and color flow doppler. The overall prevalence of cardiac disorders in dogs was 1.77% and it was 56.21% among dogs exhibiting clinical manifestations suggestive of heart disease. The highest prevalence was recorded in male, Labrador retriever between 510 years of age and lowest in female, Dachshund less than 5 years of age. Exercise intolerance and cough were the significant clinical manifestations. On radiography, cardiomegaly and pulmonary edema were the major findings observed of electrocardiography, elevated R wave was the significant observation. Echocardiography revealed dilated cardiomyopathy, an acquired heart disease as more prevalent cardiac disorder in canines.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".