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Record W3167992727 · doi:10.1016/j.ijcard.2021.05.054

Aortic angle distribution and predictors of horizontal aorta in patients undergoing transcatheter aortic valve replacement

2021· article· en· W3167992727 on OpenAlexaff
Marco Moscarelli, Francesco Gallo, Guglielmo Gallone, Won‐Keun Kim, Jörg Reifart, Verena Veulemans, Tobias Zeus, Stefan Toggweiler, Ole De Backer, Lars Søndergaard, Antonio Mangieri, Federico De Marco, Damiano Regazzoli, Bernhard Reimers, Guillem Muntané‐Carol, Rodrigo Estevez Lauriero, Xavier Armario, Darren Mylotte, Oliver D. Bhadra, Lenard Conradi, Luis Alfonso Marroquín Donday, Luis Nombela‐Franco, Marco Barbanti, Claudia Reddavid, Salvatore Brugaletta, Elisa Nicolini, Giorgos Tzanis, Josep Rodés‐Cabau, Antonio Colombo, Francesco Giannini

Bibliographic record

VenueInternational Journal of Cardiology · 2021
Typearticle
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsMedicineCardiologyInternal medicineAortic valveAortaAortic valve replacementStenosis

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.004
Threshold uncertainty score0.292

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.008
GPT teacher head0.293
Teacher spread0.285 · 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 teacher head, 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

Citations13
Published2021
Admission routes1
Has abstractno

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