Characterization of Cardiac Diseases in Dogs Prevalent in Indian Conditions
Bibliographic record
Abstract
Background: Cardiac diseases defined as structural, functional, mechanical and electrical abnormality of heart. Characterization of different cardiac diseases in dogs prevalent in North Indian conditions is least studied. Methods: Out of total 2582 registered dogs, 41 were suspected for cardiac diseases based on clinical signs. Further confirmation and characterization was done by electrocardiography, radiography, echocardiography and cardiac biomarkers. Statistical analysis was done through SPSS 23. Result: Present study inferred, Dilated cardiomyopathy (DCM) as the most prevalent cardiac affection. Left ventricular dilation, interventricular septum thinning, increased E point septal separation and left atrial enlargement were characteristic echocardiographic indices in DCM. Echocardiographic indices in hypertrophic cardiomyopathy were increased interventricular septum, left ventricular posterior wall and reduced left ventricular lumen. Labrador retriever found to be most predisposed breed for DCM while Rottweiler reported to be most affected with pericardial effusion. Cardiac Troponin-I (cTnI) was statistically (p less than 0.05) increased in all cardiac categories with cut off value above 92 ng/l indicating cardiac affection, while Lactate dehydrogenase serve as screening biochemical marker with significant increase in all the cardiac cases ranging from 291 IU/l to 586.4 IU/l.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".