Interobserver repeatability of interventricular septal wall measurements in cats
Bibliographic record
Abstract
INTRODUCTION: Clinically, echocardiography is the gold standard test for diagnosing hypertrophic cardiomyopathy in cats. Low interobserver variability for echocardiographic measurements has generally been reported in the literature. We hypothesized that interobserver variability is high when measuring the interventricular septum (IVS) thickness in cats. MATERIALS AND METHODS: Echocardiographic right-sided parasternal left ventricular (LV) outflow tract views from four cats with different LV morphologies were selected. Five measurements of the IVS in each picture were performed by 29 veterinary cardiologists and cardiology residents from different institutions. Intraclass correlation coefficient (ICC) was applied for data analysis. RESULTS: Interobserver repeatability was poor for the base of the IVS (partial ICC: 0.4) and moderate for the rest of the IVS (partial ICC: 0.6). A range of 0.7 mm between the lower and upper limits of measurements was found for each picture and region of the IVS. Around 27% of variance in measurements was associated with training location (country), whereas around 73% of the variance was attributable to the observer. STUDY LIMITATIONS: Study limitations included the use of still pictures and assessment of one echocardiographic parameter only. CONCLUSIONS: As hypothesized, the interobserver repeatability of IVS measurements using the right-sided parasternal LV outflow tract view in cats was poor to moderate. This finding is relevant when comparing and interpreting measurements obtained by different observers. Additionally, the influence of training location may need to be considered when interpreting results of variability studies involving observers from the same facility.
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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) | 0.001 | 0.001 |
| 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".