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Record W4225832278 · doi:10.1093/europace/euac030

European Heart Rhythm Association (EHRA)/Heart Rhythm Society (HRS)/Asia Pacific Heart Rhythm Society (APHRS)/Latin American Heart Rhythm Society (LAHRS) Expert Consensus Statement on the state of genetic testing for cardiac diseases

2022· article· en· W4225832278 on OpenAlexaff
Arthur A.M. Wilde, Christopher Semsarian, Manlio F. Márquez, Alireza Sepehri Shamloo, Michael J. Ackerman, Euan A. Ashley, Eduardo Back Sternick, Héctor Barajas-Martinez, Elijah R. Behr, Connie R. Bezzina, Jeroen Breckpot, Philippe Charron, Priya Chockalingam, Lia Crotti, Michael H. Gollob, Steven A. Lubitz, Naomasa Makita, Seiko Ohno, Martín Ortiz‐Genga, Luciana Sacilotto, Eric Schulze‐Bahr, Wataru Shimizu, Nona Sotoodehnia, Rafik Tadros, James S. Ware, David S. Winlaw, Elizabeth S. Kaufman, Takeshi Aiba, Andreas Bollmann, Jong‐Il Choi, Aarti Dalal, Francisco Darrieux, John Giudicessi, Mariana Guerchicoff, Kui Hong, Andrew D. Krahn, Ciorsti MacIntyre, Judith A. Mackall, Lluı́s Mont, Carlo Napolitano, Juan Pablo Ochoa, Petr Peichl, Alexandre C. Pereira, Peter J. Schwartz, Jon Skinner, Christoph Stellbrink, Jacob Tfelt‐Hansen, Thomas Deneke

Bibliographic record

VenueEP Europace · 2022
Typearticle
Languageen
FieldMedicine
TopicCardiac electrophysiology and arrhythmias
Canadian institutionsUniversity of British ColumbiaMontreal Heart InstituteUniversité de MontréalToronto General HospitalUniversity of Toronto
FundersVlaamse regeringFonds Wetenschappelijk OnderzoekNational Heart, Lung, and Blood InstituteHeart Rhythm Society
KeywordsHeart RhythmRhythmInternal medicineCardiologyChronobiologyMedicine

Abstract

fetched live from OpenAlex

International audience

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)0.022
metaresearch head score (Gemma)0.046
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 score0.022
Threshold uncertainty score0.116

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.046
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.002
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0110.005

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 head0.020
GPT teacher head0.270
Teacher spread0.250 · 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

Citations352
Published2022
Admission routes1
Has abstractyes

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