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Record W2521859253 · doi:10.5430/jbgc.v6n2p31

Utility of cardiac computed tomography to identify arrhythmia substrates for ventricular tachycardia and sudden cardiac death

2016· article· en· W2521859253 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Biomedical Graphics and Computing · 2016
Typearticle
Languageen
FieldMedicine
TopicCardiac Imaging and Diagnostics
Canadian institutionsnot available
Fundersnot available
KeywordsVentricular tachycardiaMedicineCardiologyIntracardiac injectionInternal medicineSudden cardiac deathCoronary artery diseaseCardiac arrhythmiaCardiac imagingEtiologyTachycardiaSustained ventricular tachycardiaComputed tomographyRadiologyAtrial fibrillation

Abstract

fetched live from OpenAlex

Sudden cardiac death (SCD) is the leading cause of death in the U.S., and many of these events are attributable to malignant ventricular arrhythmias such as sustained ventricular tachycardia (VT). Most of the efforts to identify arrhythmia precipitants in these patients are based on imaging to look for myocardial or coronary artery disease. As advances in cardiac computed tomography (CCT) are made, it has demonstrated its usefulness in identifying structural intracardiac pathology and measuring parameters of cardiac anatomy and function. In this article we review the different etiologies of VT/SCD that are identifiable by CCT, and its potential usefulness in the workup for VT/SCD.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.104
Threshold uncertainty score0.506

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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 head0.015
GPT teacher head0.293
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