An advanced vision of magnetocardiography as an unrivalled method for a more comprehensive non-invasive clinical electrophysiological assessment
Bibliographic record
Abstract
Decades of experimental and clinical studies, along with the most recent clinical trials, have demonstrated the diagnostic potential of magnetocardiography, particularly for the non-invasive early diagnosis of myocardial ischemia. It has also proven to be a valuable clinical tool for monitoring fetal well-being, normal growth, prenatal arrhythmias, and risk markers for sudden death. Such applications have recently received official recognition from Health Canada and the American Heart Association. This unquestionable success, and the additional evidence of magnetocardiography's high sensitivity in diagnosing infiltrative and inflammatory cardiomyopathies, has sparked renewed interest among clinicians. However, while these aforementioned applications are likely to significantly influence the broader clinical adoption of magnetocardiography, the general focus on these areas has shifted attention away from what we have always regarded as the fundamental strength of contactless cardiac magnetic field mapping: its unique ability to bridge the gap between experimental electrophysiology at the cellular level and non-invasive clinical assessments of human electrophysiology. This review aims to engage readers by sharing our vision, experience, and several key research milestones, emphasizing the lesser-explored yet significant potential of magnetocardiography. Specifically, it highlights its unique capability to detect electrically silent phenomena that may be critical for the timely and accurate identification of arrhythmogenic focal electrotonic and vortex currents, which can trigger or sustain life-threatening arrhythmias.
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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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".