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Record W2898093819 · doi:10.1016/j.jtcvs.2018.10.076

AVIATOR: An open international registry to evaluate medical and surgical outcomes of aortic valve insufficiency and ascending aorta aneurysm

2018· article· en· W2898093819 on OpenAlexfundno aff
Frederiek de Heer, Jolanda Kluin, Gébrine Elkhoury, Guillaume Jondeau, Maurice Enriquez‐Sarano, Hans‐Joachim Schäfers, Johanna J.M. Takkenberg, Emmanuel Lansac, Christian Dinges, Johannes Steindl, Rosina Ziller, Laurent De Kerchove, Taoufik Benkacem, C Coulon, Fadoua Kaddouri, Jean‐Louis Vanoverschelde, Christophe de Meester, Agnès Pasquet, Jan Nijs, Veerle Van Mosselvelde, Bart Loeys, Bart Meuris, Evi Schepmans, Klaartje Van den Bossche, Peter Verbrugghe, Wenke Goossens, Herbert Gutermann, Matteo Pettinari, Ismaı̈l El-Hamamsy, Marien Lenoir, Pierre‐Emmanuel Noly, Michaël Tousch, Pallav Shah, Munir Boodhwani, Igor Rudež, Davor Barić, Daniel Unić, Josip Varvodić, Savica Gjorgijevska, Jan Vojáček, Pavel Žáček, Mikita Karalko, Jaroslav Hlubocký, Róbert Novotný, Andrey Slautin, Said Soliman, Eric Arnaud-Crozat, Aude Boignard, Georges Fayad, Olivier Bouchot, Bernard Albat, Alain Leguerrier, Fabien Doguet, Jean‐François Fuzellier, Y Glock, Guy Fernandez, Didier Chatel, David Messika–Zeitoun, Jérôme Jouan, Isabelle Di Centa, Jean‐François Obadia, Pascal Leprince, Rémi Hoüel, Éric Bergoend, Stéphane Lopez, Alain Berrébi, Florence Tubach, Stéphanie Lejeune, Jean‐Luc Monin, Sarah Pousset, Leila Mankoubi, Milean Noghin, Christelle Diakov, Daniel Czytrom, Michael A. Borger, Diana Aicher, Frank Theisohn, Paolo Ferrero, Șerban Stoica, Maciej Matuszewski, Patrick Yiu, Mohamad Bashir, Fabrizio Ceresa, Francesco Patanè, Ruggero De Paulis, Ilaria Chirichilli, Mauro Masat, Carlo Antona, Monica Contino, Andrea Mangini, Claudia Romagnoni, Francesco Grigioni, Rubina Rosa, Yutaka Okita, Takeshi Miyairi, Takashi Kunihara, David R. Koolbergen, Mandy Marsman, Arjen L. Gökalp, Jos A. Bekkers, Liesbeth W. Duininck, Robert J.M. Klautz, Thomas van Brakel, Bardia Arabkhani, Gianclaudio Mecozzi, Ryan E. Accord, Marek Jasiński, V. V. Aminov, M. A. Svetkin, Adrián Kolesár, František Sabol, Tomáš Toporcer, Ignacio Bibiloni, Gregorio Rábago, Virginia Álvarez-Asiáin, Amaia Melero, Rafael Sádaba, José I. Aramendi, Alejandro Crespo, Carlos Porras, Arturo Evangelista Masip, Shelagh Kelley, Joseph E. Bavaria, Rita K. Milewski, Patrick Moeller, Isaac Wenger, Maurice Enriquez-Sarano, Stan Alger, Aurelie Alger, Katie Leavitt

Bibliographic record

VenueJournal of Thoracic and Cardiovascular Surgery · 2018
Typearticle
Languageen
FieldMedicine
TopicAortic Disease and Treatment Approaches
Canadian institutionsnot available
FundersCliniques Universitaires Saint-LucUniversiteit AntwerpenCentre Hospitalier Universitaire de RennesAssociation Chirurgicale Pour Le Développement et L'Amélioration des Techniques de Dépistage et de Traitement des Maladies Cardio-vasculairesDepartment of Surgery, University of ManitobaCentre Hospitalier Régional Universitaire de MontpellierUniversity of OttawaUniverzita Karlova v Praze
KeywordsAscending aortaMedicineAortic valveAortic aneurysmAneurysmAortic Valve InsufficiencyAortaSurgeryCardiologyInternal medicine

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)0.002
metaresearch head score (Gemma)0.004
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0010.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.373
Teacher spread0.329 · 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

Citations53
Published2018
Admission routes1
Has abstractno

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