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Record W4377142171 · doi:10.1016/j.hrthm.2023.03.1538

2023 HRS/APHRS/LAHRS guideline on cardiac physiologic pacing for the avoidance and mitigation of heart failure

2023· article· en· W4377142171 on OpenAlexaff
Mina K. Chung, Kristen K. Patton, Chu‐Pak Lau, Alexander Romeno Janner Dal Forno, Sana M. Al‐Khatib, Vanita Arora, Ulrika Birgersdotter‐Green, Yong‐Mei Cha, Eugene H. Chung, Edmond M. Cronin, Anne B. Curtis, Iwona Cygankiewicz, Gopi Dandamudi, Anne M. Dubin, Douglas P. Ensch, Taya V. Glotzer, Michael R. Gold, Zachary D. Goldberger, Rakesh Gopinathannair, Eiran Z. Gorodeski, Alejandra Gutiérrez, Juan C. Guzmán, Weijian Huang, Peter B. Imrey, Julia H. Indik, Saima Karim, Peter P. Karpawich, Yaariv Khaykin, Erich L. Kiehl, Jordana Kron, Valentina Kutyifa, Mark S. Link, Joseph E. Marine, Wilfried Müllens, Seung‐Jung Park, Ratika Parkash, Manuel Patete, Rajeev K. Pathak, Carlos Perona, Mark H. Schoenfeld, Swee‐Chong Seow, Win‐Kuang Shen, Morio Shoda, Jagmeet P. Singh, David J. Slotwiner, Arun Raghav Mahankali Sridhar, Uma N. Srivatsa, Eric C. Stecker, Tanyanan Tanawuttiwat, W.H. Wilson Tang, Carlos A. Tapias, Cynthia M. Tracy, Gaurav A. Upadhyay, Niraj Varma, Kevin Vernooy, Pugazhendhi Vijayaraman, Sarah Ann Worsnick, Wojciech Zaręba, Emily P. Zeitler

Bibliographic record

VenueHeart Rhythm · 2023
Typearticle
Languageen
FieldMedicine
TopicCardiac pacing and defibrillation studies
Canadian institutionsQueen Elizabeth II Health Sciences CentreSouthlake Regional Health CenterMcMaster University
FundersNational Heart, Lung, and Blood InstituteHeart Rhythm SocietyU.S. Department of Veterans Affairs
KeywordsMedicineCardiac resynchronization therapyGuidelineHeart failureCardiologyCardiac pacingInternal medicineClinical PracticeCardiomyopathyIntensive care medicineEjection fractionPhysical therapy

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)0.006
metaresearch head score (Gemma)0.016
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.029
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.016
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.004
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0030.001
Research integrity0.0070.006
Insufficient payload (model declined to judge)0.0110.009

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 head0.028
GPT teacher head0.318
Teacher spread0.290 · 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
GenreOther

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

Citations483
Published2023
Admission routes1
Has abstractno

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