3D Ultrasound: seeing is understanding—from imaging to pathophysiology to developing therapies in secondary MR
Bibliographic record
Abstract
There is a wide variability in chordal anatomy, which makes consistent non-invasive anatomic labelling and quantification difficult,1 but in the current issue of the European Heart Journal - Cardiovascular Imaging a group of very experienced investigators led by Dr Roberto Lang present an intriguing use of 3D transesophageal echocardiography (3D-TEE) to assess chordae non-invasively.2 Similar to mitral valve (MV) leaflets, chordae adapt to altered loading conditions,3,4 and now Obase et al. report that chordal remodelling appears to contribute to secondary mitral regurgitation (MR) depending on whether primary chords elongate (=less MR) or shorten (=more MR)2: with a validated and reproducible 3D-TEE method that identifies and measures primary chordae,5 the authors compared chordal lengths in normal subjects ( n = 20) with those in patients with secondary MR ( n = 38) in the setting of ischaemic ( n = 16) and non-ischaemic cardiomyopathy (CMP; n = 22). By subdividing secondary MR patients by MR severity, they found that shorter chordae to the …
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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".