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Record W2987943866 · doi:10.1016/s2352-3026(19)30219-4

Rivaroxaban compared with standard anticoagulants for the treatment of acute venous thromboembolism in children: a randomised, controlled, phase 3 trial

2019· article· en· W2987943866 on OpenAlexafffund
Christoph Male, Anthonie W.A. Lensing, Joseph S. Palumbo, Riten Kumar, Ildar Nurmeev, Kerry Hege, Damien Bonnet, Philip Connor, Hélène L. Hooimeijer, Marcela Torres, Anthony K.C. Chan, Gili Kenet, Susanne Holzhauer, Amparo Santamaría, Pascal Amédro, Elizabeth Chalmers, Paolo Simioni, Rukhmi Bhat, Donald L. Yee, O. Lvova, Jan Beyer‐Westendorf, Tina Biss, Ida Martinelli, Paola Saracco, Marjolein Peters, Krisztián Kállay, Cynthia Gauger, M. Patricia Massicotte, Guy Young, Ákos F. Pap, Madhurima Majumder, William T. Smith, Jürgen F. Heubach, Scott D. Berkowitz, Kirstin Thelen, Dagmar Kubitza, Mark Crowther, Martin H. Prins, Paul Monagle, Angelo Claudio Molinari, Ulrike Nowak- Gottl, Juan José Chain, Jeremy Robertson, Katharina Thom, Werner Streif, Rudolf Schwarz, Klaus Schmitt, Gernot Grangl, An Van Damme, Philip Maes, Veerle Labarque, Antônio Sérgio Petrilli, Sandra Loggeto, Estela Azeka, Leonardo R. Brandão, Doan Le, Christine Sabapathy, Paola Giordano, Runhui Wu, Jie Ding, Wenyan Huang, Jianhua Mao, Päivi M. Lähteenmäki, Stéphane Decramer, Toralf Bernig, Martin Chada, Gcf Chan, Krisztian Kally, Beatrice Nolan, Shoshana Revel‐Vilk, Hannah Tamary, Carina Levin, Daniela Tormene, Maria Abbattista, Andrea Artoni, Takanari Ikeyama, Ryo Inuzuka, Satoshi Yasukochi, Michelle Morales Soto, Karina Anastacia Solís‐Labastida, Monique H. Suijker, Marike Bartels, R. Y. J. Tamminga, C Heleen Van Ommen, D. Maroeska W. M. te Loo, Rui Anjos, Lyudmila Zubarovskaya, Elena Samochatova, М. Б. Белогурова, Pavel Svirin, Tatiana Shutova, В. В. Лебедев, О. Л. Барбараш, Pei Lin Koh, J. Mei, Ľudmila Podracká, Rubén Berrueco, María Florencia Fernández, Tony Frisk, Sebastian Grunt, Johannes Rischewski, Manuela Albisetti-Pedroni, Bülent Antmen, Hüseyin Tokgöz, Zeynep Karakaş, Jayashree Motwani, Michael Williams, John D. Grainger, Jeanette Payne, Mike Richards, Susan Baird, Neha Bhatnagar, Angela Aramburo, Shelley E. Crary, Tung Wynn, Shannon L. Carpenter, Sanjay Ahuja, Neil A. Goldenberg, Gary Woods, Kamar Godder, Ajovi B. Scott‐Emuakpor, Gavin D. Roach, Leslie Raffini, Nirmish Shah, Sanjay Shah, Courtney D. Thornburg, Ayesha Zia, Roger L. Berkow

Bibliographic record

VenueThe Lancet Haematology · 2019
Typearticle
Languageen
FieldMedicine
TopicBlood Coagulation and Thrombosis Mechanisms
Canadian institutionsMcMaster UniversityUniversity of AlbertaMcMaster Children's Hospital
FundersActelion PharmaceuticalsEli Lilly and CompanyCSL BehringAbbVieBristol-Myers Squibb CanadaBoehringer IngelheimAlnylam PharmaceuticalsBayerAlexion PharmaceuticalsNovartisPfizerLEO Pharma Research Foundation
KeywordsMedicineRivaroxabanVitamin K antagonistVenous thromboembolismRandomized controlled trialVenous thrombosisPulmonary embolismIntention-to-treat analysisAdverse effectSurgeryPediatricsInternal medicineWarfarinThrombosis

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: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0050.005
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0080.001

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 head0.035
GPT teacher head0.333
Teacher spread0.298 · 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 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

Citations315
Published2019
Admission routes2
Has abstractno

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