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Record W4293842487 · doi:10.1016/j.jcin.2022.06.033

Management and Outcome of Acute Ischemic Stroke Complicating Transcatheter Aortic Valve Replacement

2022· article· en· W4293842487 on OpenAlexaff
Amos Levi, Matthias Linder, Moritz Seiffert, Guy Witberg, Thomas Pilgrim, Daijiro Tomii, Yeela Talmor‐Barkan, Nicolas M. Van Mieghem, Rik Adrichem, Pablo Codner, David Hildick Smith, Sandeep Arunothayaraj, Leor Perl, Ariel Finkelstein, Itamar Loewenstein, M Findler, Lars Søndergaard, Ole De Backer, Christina Wang, Rani Barnea, Giuseppe Tarantini, Luca Nai Fovino, Hana Vaknin‐Assa, Darren Mylotte, Mattia Lunardi, Guy Raphaeli, John G. Webb, Mariama Akodad, Antonio Colombo, Antonio Mangieri, Azeem Latib, Faraj Kargoli, Francesco Giannini, Alfonso Ielasi, James Cockburn, Focko L. Higgen, Itay Aviram, Mauro Gitto, Thijmen W. Hokken, Eitan Auriel, Ran Kornowski

Bibliographic record

VenueJACC: Cardiovascular Interventions · 2022
Typearticle
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsSt. Paul's HospitalOkanagan University CollegeUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsMedicineCardiologyValve replacementInternal medicineStroke (engine)Acute strokeIschemic strokeAortic valve replacementIschemiaStenosis

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 categoriesMeta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.261
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.016
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 head0.028
GPT teacher head0.339
Teacher spread0.311 · 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.

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

Citations27
Published2022
Admission routes1
Has abstractno

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