Imaging myocardial inflammation by CMR mapping: good getting better?: Table 1
Bibliographic record
Abstract
In this issue of the European Heart Journal: Cardiovascular Imaging , Luetkens et al. 1 publish data on the diagnostic performance of cardiovascular magnetic resonance (CMR) tissue markers, specifically myocardial magnetic relaxation times, in detecting acute myocarditis. In 34 patients with clinical evidence for acute myocarditis and 50 controls, the diagnostic accuracy was found to be excellent for both current CMR markers (‘Lake Louise criteria’2) and myocardial relaxation times T1 and T2 (including the extracellular volume fraction, derived from post-contrast T1). The Lake Louise criteria yielded a diagnostic accuracy of 92% [sensitivity 82%, specificity 98%, area under the curve (AUC) 0.90]. Diagnostic accuracies of 96% were also achieved by combining relaxation times with high-signal-intensity areas in late gadolinium enhancement (LGE) images. Albeit not sensitive itself, the addition of longitudinal strain to native T1 and T2 also showed …
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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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.008 |
| 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".