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Record W4387693824 · doi:10.1016/j.jacc.2023.09.602

TCT-592 Transcatheter Aortic Valve Replacement With Balloon- Versus Self-Expandable Bioprostheses for the Treatment of Bicuspid Aortic Valve Stenosis

2023· article· en· W4387693824 on OpenAlexaff
Daniele Giacoppo, Héctor Alvarez Covarrubias, Erion Xhepa, Yuji Matsuda, Stefano Cangemi, Jonathan Michel, Anna Sannino, Johannes Ziegelmueller, Enrico Criscione, Motoki Fukutomi, Manuel Hein, Romain Didier, David Meier, Taishi Okuno, Sebastian Ludwig, Marco Ancona, Dimitry Schewel, Tommaso Fabris, Flavien Vincent, Lisa Voigtländer, Francesca Ziviello, Richard Tanner, Claudia Tamburino, Hendrik Ruge, Mattia Lunardi, Pablo Codner, Marco Barbanti, Fabian Nietlispach, Holger Nef, Ivan P. Casserly, Vasilis Babaliaros, Didier Tchétché, Rüediger Lange, Martine Gilard, Matteo Montorfano, Martin Landt, Paul Grayburn, Philipp Ruile, Nicolas M. Van Mieghem, Francesco Bedogni, George Dangas, Corrado Tamburino, Niklas Schofer, Francesco Burzotta, Éric Van Belle, Franz‐Josef Neumann, Ran Kornowski, Flavio Ribichini, Darren Mylotte, Stephan Windecker, Gert Richardt, Lars Søndergaard, John G. Webb, Giuseppe Tarantini, Thomas Pilgrim, Roxana Mehran, Davide Capodanno, Adnan Kastrati, Michael Joner, Mark Spence, Markus Kasel

Bibliographic record

VenueJournal of the American College of Cardiology · 2023
Typearticle
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsSt. Paul's Hospital
Fundersnot available
KeywordsMedicineBicuspid aortic valveStenosisCardiologyBalloonValve replacementInternal medicineBicuspid valveAortic valve replacement

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.313
Teacher spread0.292 · 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 designObservational
Domainnot available
GenreEmpirical

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
Published2023
Admission routes1
Has abstractno

Explore more

Same venueJournal of the American College of Cardiology→Same topicCardiac Valve Diseases and Treatments→French-language works237,207→