Unanticipated stenosis of the systemic arterial supply in scimitar syndrome
Bibliographic record
Abstract
A 28-year-old woman, with known Scimitar syndrome, was evaluated for moderate exercise intolerance. Examination was notable for grade 2/6 systolic murmur over the pulmonary area. The electrocardiogram was unremarkable. Chest X-ray demonstrated dextroposition of the heart with a shadow suggestive of the scimitar vein. Transthoracic echocardiogram was technically challenging with no evidence of pulmonary hypertension or intracardiac shunts. Cardiovascular magnetic resonance showed moderately dilated right ventricle with normal systolic function and hypoplasia of the right lung and right pulmonary artery (PA) (Supplementary material online, Video 1). The right pulmonary veins (PVs) joined in a confluence and drained into the right atrium (RA) flush with the inferior vena cava junction above the diaphragm. The left PVs drained normally into the left atrium. The Qp/Qs ratio was 1.5:1. (PanelsA–C, Supplementary material online, Video 2). The entire right lung was supplied by the right PA except for a small area of the basal zone which was fed by multiple small systemic arterial collaterals arising from the celiac axis. These collaterals demonstrated multiple severe stenoses and post-stenotic aneurysmal dilatation throughout their course. This was confirmed by cardiac computed tomography (CCT) (Panels D and E). CCT revealed normal bronchial anatomy and lung parenchyma.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".