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Record W2140187246

Body surface potential mapping and computer simulation of human ventricular fibrillation

2006· article· en· W2140187246 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueComputing in Cardiology Conference · 2006
Typearticle
Languageen
FieldMedicine
TopicCardiac electrophysiology and arrhythmias
Canadian institutionsDalhousie University
Fundersnot available
KeywordsVentricular fibrillationBody surfaceCardiologyFibrillationBidomain modelDefibrillationElectrocardiographyInternal medicineHuman heartBiomedical engineeringPhysicsMedicineAtrial fibrillationMathematics
DOInot available

Abstract

fetched live from OpenAlex

Our aim was to study the electrical characteristics of human ventricular fibrillation (VF) by means of body surface potential mapping and heart-model simulations. We acquired 120-lead ECG data on the chest surface of patients undergoing controlled testing of implantable defibrillators. VF was induced by burst pacing, and ECGs were recorded for 5 to 7 seconds before the device delivered a rescue shock. We then used orthogonal decomposition to characterize spatial and temporal features of ECGs, and inverse solution to derive epicardial potential maps. To gain insight into mechanisms of VF, we used an anisotropic bidomain model of the human ventricular myocardium, featuring 5 ionic currents. The model showed meandering VF scroll waves exhibiting break-up and coalescence according to choice of ionic-current parameters. This combination of experiments and simulations offers a unique perspective on the origin of spatial patterns of ECG during VF.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.407
Threshold uncertainty score0.424

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.014
GPT teacher head0.263
Teacher spread0.250 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it