The pioneering work of George Mines on cardiac arrhythmias: groundbreaking ideas that remain influential in contemporary cardiac electrophysiology
Bibliographic record
Abstract
George Mines was a pioneering physiologist who, despite an extremely short period of professional activity and only primitive experimental methodology, succeeded in formulating concepts that continue to be of great influence today. Here, we review some of his most important discoveries and their impact on contemporary concepts and clinical practice. Mines' greatest contribution was his conceptualization and characterization of circus movement reentry. His observations and ideas about the basis for cardiac reentrant activity underlie how we understand and manage a wide range of important clinical rhythm disturbances today. The notions he introduced regarding the influence of premature extrastimuli on reentry (termination, resetting and entrainment) are central to contemporary assessment of arrhythmia mechanisms in clinical electrophysiology laboratories and modern device therapy of cardiac tachyarrhythmias. Refinements of his model of reentry have led to sophisticated biophysical theories of the mechanisms underlying cardiac fibrillation. His seminal observations on the influence of electrolyte derangements and autonomic tone on the heart are relevant to our understanding of the physiology and pharmacology of arrhythmias caused by cardiac pathology. In this era of advanced technology, it is important to appreciate that ideas of lasting impact come from great minds and do not necessarily require great tools.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.007 |
| 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".