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Record W4396606742 · doi:10.1016/j.jscai.2024.101665

C-36 | Association between coronary revascularization and reduction in ventricular arrhythmias in stable coronary artery disease patients: A systematic review and meta-analysis

2024· review· en· W4396606742 on OpenAlexaboutno aff
Joey Junarta, Muhammad Umer Siddiqui, Ehab Abaza, Anjani Patel, Peter Zhang, Louai Razzouk, Sunil V. Rao

Bibliographic record

VenueJournal of the Society for Cardiovascular Angiography & Interventions · 2024
Typereview
Languageen
FieldMedicine
TopicCardiac Imaging and Diagnostics
Canadian institutionsnot available
Fundersnot available
KeywordsCardiologyInternal medicineMedicineCoronary artery diseaseMeta-analysisRevascularizationMyocardial infarction

Abstract

fetched live from OpenAlex

Ventricular arrhythmias (VA) are a major cause of morbidity and mortality in coronary artery disease (CAD) patients. The utility of coronary revascularization in reducing VA in stable CAD patients who do not present with acute coronary syndrome (ACS) and are not post-cardiac arrest is unclear.

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)0.013
metaresearch head score (Gemma)0.042
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.022
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.042
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0220.056
Bibliometrics0.0060.008
Science and technology studies0.0010.001
Scholarly communication0.0050.002
Open science0.0020.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0100.001

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 head0.035
GPT teacher head0.306
Teacher spread0.271 · 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 designMeta-analysis
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

Citations0
Published2024
Admission routes1
Has abstractyes

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