Contemporary considerations for the use of cardiovascular magnetic resonance imaging during pregnancy
Bibliographic record
Abstract
Cardiovascular imaging during pregnancy is frequently used to help direct diagnosis and management for women with known or suspected cardiac disease. Although echocardiography is the most commonly used imaging modality in pregnancy, cardiovascular magnetic resonance imaging is an important and increasingly used tool, which can provide complementary, and oftentimes incremental, information regarding cardiovascular anatomy, ventricular function, and vascular flows. Advantages of cardiovascular magnetic resonance imaging over echocardiography and other imaging techniques include superior reproducibility, excellent cross-sectional evaluation of cardiac structures, high spatial resolution, and lack of ionizing radiation (a limitation of computed tomography and conventional catheter-based angiography). Cardiovascular magnetic resonance imaging in the absence of gadolinium-based contrast agents poses no known risk to the mother or fetus and its applications in pregnancy are expanding. Clinicians should be familiar with the role of cardiovascular magnetic resonance imaging in pregnancy to optimize and enhance care for mothers with heart disease.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".