A Retrospective Analysis of Dilated Cardiomyopathy in Labrador Retrievers
Bibliographic record
Abstract
The present study was conducted to record the incidence, clinical presentation, electrocardiographic, radiographic, laboratory, two dimensional echocardiography, M-mode echocardiography, pulsed wave Doppler and color flow Doppler findings in Labrador Retrievers with Dilated Cardiomyopathy (DCM) for a period of five years from 2013 to 2018. It included 210 healthy dogs and 327 confirmed cases of DCM. The incidence of dilated cardiomyopathy in Labrador Retrievers was found to be 7.49 per cent in the present study. On radiography, cardiomegaly and pulmonary edema were the major findings observed. In echocardiography, increased left ventricular end diastolic dimension and systolic dimension, reduced fraction shortening, increased E-point sepal separation, increased Left atrium (LA)/Aorta (AO) ratio, decreased ejection fraction, increased end diastolic volume and end systolic volume were noticed. On pulsed wave Doppler echocardiography reduced pulmonary artery (PA), Aorta (AO), left ventricular outflow tract (LVOT), right ventricular outflow tract (RVOT) velocities were recorded. Mild to moderate regurgitation was observed in Mitral and Tricuspid valve by color flow Doppler echocardiography. M-mode derived chamber dimensions, E-point septal separation, ejection fraction, fractional shortening were reliable parameters in diagnosing Dilated Cardiomyopathy in Labrador Retrievers. Pulsed wave Doppler and color flow Doppler were useful in assessing velocity and flow pattern across valves.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".