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Record W1738592499 · doi:10.1109/cic.1990.144235

A computer simulation of the time-dependent conduction properties of the atrioventricular (AV) node

2002· article· en· W1738592499 on OpenAlexafffund
D Papadatos, Mario Talajic, C Villemaire, Stanley Nattel, Leon Glass

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicCardiac electrophysiology and arrhythmias
Canadian institutionsMontreal Heart InstituteMcGill University
FundersMedical Research CouncilFondation pour la Recherche MédicaleHeart and Stroke Foundation of Canada
KeywordsThermal conductionBeat (acoustics)Node (physics)Atrioventricular nodeNODALStimulationComputer scienceBiomedical engineeringCardiologyPhysicsInternal medicineMedicineAcousticsThermodynamicsTachycardia

Abstract

fetched live from OpenAlex

The conduction behavior of the AV node was studied in autonomically blocked dogs during rapid atrial stimulation. It is shown that conduction time through the node depends on the recovery time since the last ventricular activation (recovery), and also on the time-dependent changes of the node due to lengthy prior stimulation, which leads to an increased conduction time (fatigue). A theoretical model is presented that incorporates both recovery and fatigue which can be used to predict AV modal behavior, on a beat-to-beat basis given any simulation history. The validity of this model was tested by attempting to simulate the time-dependent changes observed in AV nodal conduction during Wenckebach pattern generation (second degree AV nodal block). The predictions showed good agreement with the experimental observations.>

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)0.001
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.016
GPT teacher head0.215
Teacher spread0.199 · 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

Citations0
Published2002
Admission routes2
Has abstractyes

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