Magnetic resonance imaging in vascular biology☆
Bibliographic record
Abstract
Symptoms are only the tip of the iceberg in atherosclerotic disease. Beneath the surface are multiple patho-physiological processes taking place in and around the vessel wall. The increasing knowledge in the field of vascular biology also reveals new imaging targets as biological markers of the disease. Promising targets particularly relate to the early detection of subjects at risk and monitoring of therapeutical efforts. Among other imaging modalities magnetic resonance imaging (MRI) is an emerging tool with strong potential and a favourable safety profile. This article summarizes the different approaches of imaging various facets of atherosclerotic disease by MRI. In particular, endothelial function, arterial stiffness, vessel remodeling, angiogenesis inside the vessel wall, vessel stenosis and plaque characterization are addressed. As such MRI is a very versatile diagnostic tool for vascular biology research with high diagnostic accuracy and reproducibility of its results. Moreover, MRI allows for comprehensive studies, applying several techniques within one exam.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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".