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Record W2794851119 · doi:10.22489/cinc.2017.019-015

Asymmetry of Unipolar Electrograms in a Thin Tissue with Epicardial-Endocardial Activation Delay

2017· article· en· W2794851119 on OpenAlexafffund
Éric Irakoze, Halekote Ramesh Chirasvi, Vincent Jacquemet

Bibliographic record

VenueComputing in cardiology · 2017
Typearticle
Languageen
FieldMedicine
TopicCardiac electrophysiology and arrhythmias
Canadian institutionsUniversité de MontréalHôpital du Sacré-Cœur de Montréal
FundersNatural Sciences and Engineering Research Council of CanadaMitacs
KeywordsAsymmetryMaterials sciencePhysics

Abstract

fetched live from OpenAlex

Experimental evidences suggest the occurrence of epicardial-endocardial activation delays in structurally remodeled atrial tissue.Our aim was to investigate the consequences of this delay on electrogram morphology.We created a 50×50×2 mm monodomain model of atrial tissue composed of an epicardial and an endocardial layer (1 mm thickness each) with different conductivities.Plane waves with epicardial-endocardial delays were simulated.Unipolar electrograms were computed.Simulated electrogram asymmetry was compared to a theoretical formula that expresses asymmetry in terms of the angle between the equivalent dipole and the tissue surface.The results showed that electrogram asymmetry is strongly related to the sine of the angle of the equivalent dipole.Further analysis suggests that epicardialendocardial delay and transmural coupling are important determinants of asymmetry.These findings contribute to the interpretation of unipolar electrogram morphology.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.289
Teacher spread0.278 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2017
Admission routes2
Has abstractyes

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