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Record W3193942184 · doi:10.1093/ejcts/ezab389

2021 ESC/EACTS Guidelines for the management of valvular heart disease

2021· article· en· W3193942184 on OpenAlexaff
Friedhelm Beyersdorf, Milan Milojevic, Fabien Praz, Stephan Baldus, Johann Bauersachs, Davide Capodanno, Lenard Conradi, Michele De Bonis, Ruggero De Paulis, Victoria Delgado, Martine Gilard, Kristina H. Haugaa, Anders Jeppsson, Peter Jüni, Luc Piérard, Bernard Prendergast, Rafael Sádaba, Christophe Tribouilloy, Franz-Josef Neumann, Patrick O. Myers, Magdy Abdelhamid, Stephan Achenbach, Riccardo Asteggiano, Fabio Barili, Michael A. Borger, Thierry Carrel, Jean‐Philippe Collet, Dan Foldager, Gilbert Habib, Christian Hassager, Alar Irs, Bernard Iung, Marjan Jahangiri, Hugo A. Katus, Konstantinos C. Koskinas, Steffen Massberg, Christian Mueller, Jens Cosedis Nielsen, Philippe Pîbarot, Amina Rakisheva, Marco Roffi, Andrea Rubboli, Е. V. Shlyakhto, Matthias Siepe, Marta Sitges, Lars Søndergaard, Miguel Sousa‐Uva, Guiseppe Tarantini, Jose Luis Zamorano, Stephan Baldus, Johann Bauersachs, L. Pierard, Christophe Tribouilloy

Bibliographic record

VenueEuropean Journal of Cardio-Thoracic Surgery · 2021
Typearticle
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsUniversity of Toronto
FundersTürk Kardiyoloji DerneğiBritish Cardiovascular Society
KeywordsMedical prescriptionMedicineHealth careAmbiguityContradictionHealth professionalsMedical educationPsychologyPublic relationsFamily medicinePolitical scienceNursingLawComputer science

Abstract

fetched live from OpenAlex

Association for Acute CardioVascular Care (ACVC), European Association of Cardiovascular Imaging (EACVI), European Association of Percutaneous Cardiovascular Interventions (EAPCI), European Heart Rhythm Association (EHRA), Heart Failure Association (HFA).Councils: Council on Valvular Heart Disease.

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)0.008
metaresearch head score (Gemma)0.032
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: Methods · Consensus signal: none
Teacher disagreement score0.047
Threshold uncertainty score0.158

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.032
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0070.004
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0030.002
Research integrity0.0070.007
Insufficient payload (model declined to judge)0.0470.052

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 head0.076
GPT teacher head0.389
Teacher spread0.314 · 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
GenreMethods

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

Citations635
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueEuropean Journal of Cardio-Thoracic Surgery→Same topicCardiac Valve Diseases and Treatments→French-language works237,207→