Pulmonary Hypertension Findings Detected by F-18 FDG PET Scan
Bibliographic record
Abstract
A 72-year-old female patient had severe pulmonary hypertension on transthoracic echocardiography with a pulmonary arterial pressure of 125 mm Hg, moderate tricuspid regurgitation, and a moderately dilated, mildly hypokinetic right ventricle (RV). A CT scan, performed to assess the etiology of the pulmonary hypertension, revealed a right middle lobe lung nodule and enlarged mediastinal lymph nodes. A subsequent F-18 FDG PET scan demonstrated the right middle lobe lung nodule and the mediastinal adenopathy to be FDG-avid, but a striking incidental finding on this study was intense RV FDG uptake, secondary to RV hypertrophy and strain.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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; both teacher heads agree on what is shown here.
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".