Canine mitral valve size as measured by computed tomography
Bibliographic record
Abstract
OBJECTIVE: To measure the mitral annulus in dogs. Our hypothesis was that mitral measurement would be possible and consistent among observers using CT. SAMPLE: Thoracic CT scans of dogs without known heart disease. PROCEDURES: Five trained investigators measured 4 aspects of the mitral valve and the fourth thoracic vertebrae (T4) length using multiplanar reformatting tools. Ten randomly chosen animals were measured by all investigators to determine interobserver reliability. RESULTS: There were 233 CT scans eligible for inclusion. Dogs weighed 2 to 96 kg (mean, 28.1 kg), with a variety of breeds represented. Golden Retrievers (n = 28) and Labrador Retrievers (n = 37) were overrepresented. The intraclass correlations were all greater than 0.9, showing excellent agreement between observers. The means and SDs of each measurement were as follows: trigone-to-trigone distance, 17.2 ± 4.7 mm; the remaining circumference, 79.0 ± 17.5 mm; commissure-to-commissure distance, 30.8 ± 6.5 mm; septal leaflet-to-lateral leaflet distance, 26.3 ± 6.0 mm; T4 length, 16.9 ± 3.1 mm; and the total circumference normalized by T4, 5.7 ± 0.7 mm. CLINICAL RELEVANCE: This study provides information that may help in the development of future treatment for mitral valve dysfunction and subsequent annular enlargement.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".