Modelling anatomic reentry: a 3D study on a virtual slab
Bibliographic record
Abstract
Lethal arrhythmias (abnormal heart rhythms) are associated with structural heart disease and can be related to heart rates higher than 150 beats/min. This provides a strong motivation to study: i) physical conditions that favor their inducibility, and ii) physical parameters which determine their cycle length. In this work we developed a three dimensional (3D) theoretical model that predicts, based on Finite Element methods, abnormal propagation of action potential (AP) associated with anatomic reentry (a re-excitation of the myocardium, caused by waves circulating around infarct scars through a narrow channel of slow conduction). Reentries associated with the ventricles generate high heart rhythms called ventricular tachycardias. Via simulations of electrical activity, we studied the physical conditions favoring the inducibility of reentrant VT. The simulations were produced for a 3D virtual slab of tissue (2.5x2.5x1cm). Simulation results show that the VT cycle length depends on the perimeter of the obstacles and the conduction velocity in the channel. We studied the effect of the physical parameters such as tissue conductivity, anisotropy of the fibers and cross-section of the channel (called isthmus) on tissue conduction velocity, and further on the VT cycle length.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".