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Record W3013808242 · doi:10.1111/pace.13907

Trans‐myocardial bipolar electrogram: A strategy for mapping and determining efficacy of bipolar ablation of deep foci

2020· article· en· W3013808242 on OpenAlexaff
Mahmoud Bokhari, Abhishek Bhaskaran, Gregory Gorth, Stéphane Massé, Eugene Downer, Kumaraswamy Nanthakumar

Bibliographic record

VenuePacing and Clinical Electrophysiology · 2020
Typearticle
Languageen
FieldMedicine
TopicCardiac Arrhythmias and Treatments
Canadian institutionsToronto General HospitalUniversity Health Network
Fundersnot available
KeywordsMedicineAblationCardiologyInternal medicineVentricular tachycardiaTachycardiaCatheter ablationRf ablation

Abstract

fetched live from OpenAlex

Mapping and ablation of intramural ventricular tachycardia (VT) remain a challenge. We developed a trans-myocardial electrogram recording across distal tips of two separate ablation catheters placed on contralateral sides of the myocardium to record a trans-myocardial bipole and a novel pacing electrode configuration. This trans-myocardial bipole was applied during bipolar ablation in a patient with septal VT. Local activation in this trans-myocardial bipole was similar to the earliest activation recorded from detailed activation maps from both sides of the septum. Pacing from this trans-myocardial bipole resulted in a perfect morphology match. After bipolar ablation, the trans-myocardial bipolar voltage decreased by 82%, and pacing threshold increased by 800%. These findings correlated with VT noninducibility.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.038
GPT teacher head0.331
Teacher spread0.293 · 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 designBench or experimental
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

Citations4
Published2020
Admission routes1
Has abstractyes

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