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Rivaroxaban with or without aspirin in patients with stable peripheral or carotid artery disease: an international, randomised, double-blind, placebo-controlled trial
Sonia S. Anand, Jackie Bosch, John W. Eikelboom, Stuart J. Connolly, Rafael Díaz, Peter Widimsky, Victor Aboyans, Marco Alings, Ajay K. Kakkar, Katalin Keltai, Aldo P. Maggioni, Basil S. Lewis, Stefan Störk, Jun Zhu, Patricio López‐Jaramillo, Martin O’Donnell, Patrick Commerford, Dragoş Vinereanu, Nana Pogosova, Lars Rydén, Keith A.A. Fox, Deepak L. Bhatt, Frank Misselwitz, George Varigos, Thomas Vanassche, Álvaro Avezum, Edmond Chen, Kelley R. Branch, Darryl P. Leong, Shrikant I. Bangdiwala, Robert G. Hart, Salim Yusuf, JORGELINA SALA, Luis R Cartasegna, MARISA VICO, Miguel Hominal, Eduardo Hasbani, Alberto Caccavo, Cesar Javier Zaidman, DANIEL VOGEL, Adrian D. Hrabar, Pablo Schygiel, Carlos Alberto Cuneo, Hugo A Luquez, Ignacio MacKinnon, Rodolfo Andrés Ahuad Guerrero, Juan Pablo Costabel, INES PALMIRA BARTOLACCI, Oscar Montaña, María Antonietta Barbieri, Oscar Gómez Vilamajó, RUBEN OMAR GARCIA DURAN, Lilia Beatriz Schiavi, Marcelo Garrido, ADRIAN INGARAMO, Anselmo P. 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Brown, Robert Petrella, JOSEPH A RICCI, Anthony Glanz, Nicolas Noiseux, Kevin R. Bainey, Fatima Merali, Michael Heffernan, Anthony Della Siega, Gilles R. Dagenais, François Dagenais, STEEVE BRULOTTE, MICHEL NGUYEN, Michael Hartleib, Randolph Guzman, Ronald Bourgeois, Dennis Rupka, Yaariv Khaykin, Gilbert Gosselin, Thao Huynh, CLAUDE PILON, JEAN CAMPEAU, FRANCIS PICHETTE, ARIEL DIAZ, James P. Johnston, PRAVIN SHUKLE, Gregory Hirsch, Paul Rheault, W Czarnecki, Annie Roy, SHAH NAWAZ, STEPHEN FREMES, Dinkar Shukla, GABRIEL JANO, Jorge Cobos, Ramón Corbalán, MARCELO MEDINA, LEONARDO NAHUELPAN, Carlos A. 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Hammett, Rohan Poulter, Seshasayee Narasimhan, HENRIK WIGGERS, Henrik Kim Nielsen, Gunnar Gislason, Lars Køber, Kim Christian Houlind, VIBEKE BOENELYKKE SOERENSEN, Ulrik Dixen, Jens Refsgaard, Elisabeth Louise Zeuthen, PETER SOEGAARD, Marián Hranai, Ľudovít Gašpar, Daniel Pella, KATARINA HATALOVA, ERIKA DROZDAKOVA, Ioan Mircea Coman, DOINA DIMULESCU, Mircea Cintezǎ, Crina Sinescu, CATALINA ARSENESCU, Imre Benedek, Elena Bobescu, Dan Dobreanu, Dan Gaiță, Adrian Corneliu Iancu, ADRIANA ILIESIU, Daniel Lighezan, Lucian Petrescu, Octavian M. Pirvu, IULIA TEODORESCU, Dan Tesloianu, M. Vintila, Ovidiu Chioncel
Bibliographic record
VenueThe Lancet · 2017
Typearticle
Languageen
FieldMedicine
TopicCerebrovascular and Carotid Artery Diseases
Canadian institutionsHamilton General HospitalHamilton Health SciencesMcMaster UniversityPopulation Health Research Institute
Fundersnot available
KeywordsRivaroxabanMedicineAspirinPlaceboArterial diseaseDouble blindInternal medicineCarotid artery diseasePeripheralCardiologyVascular diseaseCarotid arteriesAnesthesiaAtrial fibrillationWarfarinCarotid endarterectomyAlternative medicinePathology
Abstract
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 imitationNot 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: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.032
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.005 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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 head0.036
GPT teacher head0.304
Teacher spread0.268 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine 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 designRandomized trial
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
Citations880
Published2017
Admission routes1
Has abstractno