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Record W4403739474 · doi:10.1016/j.hroo.2024.10.008

Cardiac venous system mapping for ventricular arrhythmia localization

2024· review· en· W4403739474 on OpenAlexaff
Matthew Hanson, Carli M. Peters, Andrés Enríquez, Fermin C. García

Bibliographic record

VenueHeart Rhythm O2 · 2024
Typereview
Languageen
FieldMedicine
TopicCardiac Arrhythmias and Treatments
Canadian institutionsQueen's University
Fundersnot available
KeywordsCardiologyInternal medicineCardiac arrhythmiaMedicineAtrial fibrillation

Abstract

fetched live from OpenAlex

The coronary venous system offers a route for mapping and ablation of ventricular arrhythmias with suspected epicardial or intramural origins. Coronary venous mapping helps the operator to select the best ablation approach, decide when percutaneous epicardial access may be necessary and provides an opportunity for therapeutic interventions, including radiofrequency application inside the coronary veins or ethanol infusion. In this article we review the anatomy of the coronary venous system, the scenarios in which coronary venous mapping can be helpful and the technical aspects involved in coronary venous mapping.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.002

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 head0.328
Teacher spread0.289 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations3
Published2024
Admission routes1
Has abstractyes

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