Assessment of Cardiac Computed TomographyMyocardial Perfusion Imaging
Bibliographic record
Abstract
Cardiac computed tomography (CT) has evolved rapidly over the last decade into a reliable imaging modality for the non-invasive assessment of coronary artery disease. With the advancement in multi-detector CT technology, there has developed an increasing body of evidence that suggests that the role of cardiac CT can be extended to include functional assessment of the myocardium not only at rest but also during stress. Simultaneous anatomical and functional assessment approaches will have a number of advantages such as evaluation of the transmural extent of myocardial perfusion defects (including small subendocardial perfusion defects), reduced risk associated with multiple sources of radiation, and short image acquisition time. Although initial results hold some promise, CT myocardial perfusion imaging is a modality in the early stages of development and further work and studies are required to define, validate, and optimize this technique. This review will provide an overview of this novel perfusion imaging method, its underlying principles, evolution, limitations and future directions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".