MétaCan
Menu
Back to cohort
Record W4293513031 · doi:10.1016/j.ahj.2022.08.010

Characterization of arrhythmia substrate to ablate persistent atrial fibrillation (COAST-AF): Randomized controlled trial design and rationale

2022· article· en· W4293513031 on OpenAlexafffund
Pablo B. Nery, George A. Wells, Atul Verma, Jacqueline Joza, Girish M. Nair, George D. Veenhuyzen, Jason G. Andrade, Isabelle Nault, Jorge Wong, Markus B. Sikkel, Vidal Essebag, Laurent Macle, John L. Sapp, Jean-François Roux, Allan C. Skanes, Paul Angaran, Paul Novak, Damian Redfearn, Mehrdad Golian, Calum J. Redpath, Marcio Sturmer, David H. Birnie

Bibliographic record

VenueAmerican Heart Journal · 2022
Typearticle
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsSt. Michael's HospitalUniversity of TorontoWestern UniversityQueen Elizabeth II Health Sciences CentreUniversité de MontréalUniversity of OttawaMcGill University Health CentreHôpital du Sacré-Cœur de MontréalMcMaster UniversityHamilton Health SciencesInstitut universitaire de cardiologie et de pneumologie de QuébecKingston General HospitalUniversity of CalgaryVancouver General HospitalCentre Hospitalier Universitaire de SherbrookeMontreal Heart InstituteUniversity of British ColumbiaLibin Cardiovascular Institute of Alberta
FundersCanadian Institutes of Health ResearchUniversity of Ottawa Heart Institute Foundation
KeywordsMedicineAtrial fibrillationAtrial tachycardiaCatheter ablationAblationCardiologyPulmonary veinInternal medicineAtrial flutterRandomized controlled trialSinus rhythmMulticenter trialCatheterSurgeryMulticenter study

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.027
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.027
Threshold uncertainty score0.144

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0270.024
Meta-epidemiology (narrow)0.0040.001
Meta-epidemiology (broad)0.0080.006
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0030.003
Open science0.0020.001
Research integrity0.0060.005
Insufficient payload (model declined to judge)0.0070.001

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 head0.044
GPT teacher head0.304
Teacher spread0.260 · 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 designRandomized trial
Domainnot available
GenreProtocol

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
Published2022
Admission routes2
Has abstractno

Explore more

Same venueAmerican Heart JournalSame topicAtrial Fibrillation Management and OutcomesFrench-language works237,207