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Record W3130386910 · doi:10.1016/j.jcin.2020.11.046

Ticagrelor Monotherapy Versus Dual-Antiplatelet Therapy After PCI

2021· review· en· W3130386910 on OpenAlexaff
Marco Valgimigli, Roxana Mehran, Anna Franzone, Bruno R. da Costa, Usman Baber, Raffaele Piccolo, Eugène McFadden, Pascal Vranckx, Dominick J. Angiolillo, Sergio Leonardi, Davide Cao, George Dangas, Shamir R. Mehta, Patrick W. Serruys, C. Michael Gibson, Samin K. Sharma, Christian W. Hamm, Richard Shlofmitz, Christoph Liebetrau, Carlo Briguori, Luc Janssens, Kurt Huber, Maurizio Ferrario, Vijay Kunadian, David J. Cohen, Aleksander Żurakowski, Keith G. Oldroyd, Yaling Han, Dariuz Dudek, Samantha Sartori, Brian Kirkham, Javier Escaned, Dik Heg, Stephan Windecker, Stuart Pocock, Peter Jüni, Michael C. Gibson, Adnan Kastrati, Mitchel Krucoff, Magnus Öhman, Paul A. Gurbel, Timothy D. Henry, David J. Moliterno, Steven O. Marx, Bruce Darrow, Nicola Corvaja, Douglas DeStefano, Newsha Ghodsi, Jose Meller, Theresa Franklin-Bond, Jin Young, Zaha Waseem, Giora Weisz, Ran Kornowski, Upendra Kaul, Bernhard Witzenbichler, Vladimír Džavík, Robert Gil, Gennaro Sardella, Edouard Benit, Roberto Diletti, Marcello Dominici, Ton Slagboom, Paweł Buszman, Leonardo Bolognese, Carlo Tumscitz, Krzysztof Bryniarski, Adel Aminian, Mathias Vrolix, Ivo Petrov, Scot Garg, Christoph Naber, Janusz Prokopczuk, Philippe Gabríel Steg

Bibliographic record

VenueJACC: Cardiovascular Interventions · 2021
Typereview
Languageen
FieldMedicine
TopicAntiplatelet Therapy and Cardiovascular Diseases
Canadian institutionsMcMaster UniversityHamilton Health SciencesSt. Michael's Hospital
FundersJanssen PharmaceuticalsNational Human Genome Research InstituteAmarin PharmaAbbott VascularGE HealthcareSt. Jude MedicalNational Center for Advancing Translational SciencesJohnson and JohnsonNational Institutes of HealthDefence Science InstituteDuke Clinical Research InstituteEisaiJanssen Scientific AffairsBritish Heart FoundationOrbusNeichSiemens Medical Solutions USAMedicines CompanyBoston Scientific CorporationNovartis Pharmaceuticals CorporationEli Lilly and CompanyFoundation for Cardiovascular ResearchBayerGilead SciencesUniversity of FloridaMedtronicAbbott LaboratoriesCSL BehringChiesi FarmaceuticiAstraZenecaBristol-Myers SquibbScott R. MacKenzie FoundationPortola PharmaceuticalsBoehringer IngelheimAmgenMerck
KeywordsTicagrelorConventional PCIMedicineDual (grammatical number)CardiologyInternal medicinePercutaneous coronary interventionMyocardial infarction

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.140
GPT teacher head0.387
Teacher spread0.247 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations37
Published2021
Admission routes1
Has abstractno

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