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Record W2139957955 · doi:10.1016/s0140-6736(11)61931-4

Interleukin-6 receptor pathways in coronary heart disease: a collaborative meta-analysis of 82 studies

2012· review· en· W2139957955 on OpenAlexaff
Nadeem Sarwar, Adam S. Butterworth, Daniel F. Freitag, John Gregson, Peter Willeit, Donal Gorman, Pei Gao, Danish Saleheen, Augusto Rendon, Christopher P. Nelson, Peter S. Braund, Alistair S. Hall, Daniel I. Chasman, John C. Chambers, Emelia J. Benjamin, Paul W. Franks, Robert Clarke, Arthur A.M. Wilde, Mieke D. Trip, Maristella Steri, Jacqueline C.M. Witteman, Lu Qi, C. Ellen van der Schoot, Ulf dé Fairé, Jeanette Erdmann, Heather M. Stringham, Wolfgang Köenig, Daniel J. Rader, David Melzer, David Reich, Bruce M. Psaty, Marcus E. Kleber, Demosthenes B. Panagiotakos, Johann Willeit, Patrik Wennberg, Mark Woodward, Svetlana Adamovic, Eric B. Rimm, Tom Meade, Richard F. Gillum, Jonathan A. Shaffer, Albert Hofman, Altan Onat, Johan Sundström, Sylvia Wassertheil‐Smoller, Dan Mellström, John Gallacher, Mary Cushman, Russell P. Tracy, Jussi Kauhanen, Magnus K. Karlsson, Jukka T. Salonen, Lars Wilhelmsen, Philippe Amouyel, Bernard Cantin, Lyle G. Best, Yoav Ben‐Shlomo, JoAnn E. Manson, Paul I. W. de Bakker, Christopher J. O’Donnell, Anthony G. Wilson, Themistocles L. Assimes, John-Olov Jansson, Claes Ohlsson, Åsa Tivesten, Östen Ljunggren, Muredach P. Reilly, Anders Hamsten, Erik Ingelsson, François Cambien, Joseph Hung, G. Neil Thomas, Michael Boehnke, Heribert Schunkert, Folkert W. Asselbergs, John J.P. Kastelein, Vilmundur Guðnason, Veikko Salomaa, Tamara B. Harris, Jaspal S. Kooner, Kristine H. Allin, Jemma C. Hopewell, Alison H. Goodall, Paul M. Ridker, Hilma Hólm, Hugh Watkins, Willem H. Ouwehand, N. J. Samani, Stephen Kaptoge, Emanuele Di Angelantonio, Olivier Harari

Bibliographic record

VenueThe Lancet · 2012
Typereview
Languageen
FieldMedicine
TopicAdipokines, Inflammation, and Metabolic Diseases
Canadian institutionsUniversité Laval
FundersNational Heart, Lung, and Blood InstituteNIHR Cambridge Biomedical Research CentreMedical Research CouncilMerck Sharp and DohmeTerveyden ja hyvinvoinnin laitosSchool of Medicine, Stanford UniversityHjartaverndSkånes universitetssjukhusHarokopio UniversityUniversität UlmGöteborgs UniversitetEvelyn TrustUniversität zu LübeckNational and Kapodistrian University of AthensKarolinska InstitutetUniversiteit van AmsterdamNational Institute for Health and Care ResearchGentofte HospitalInstitut National de la Santé et de la Recherche MédicaleUmeå UniversitetSchool of Medicine, Boston UniversityEuropean CommissionSahlgrenska UniversitetssjukhusetErasmus Medisch CentrumUniversity of OxfordLunds UniversitetUniversity of ExeterFogarty International CenterLondon School of Hygiene and Tropical MedicineBupa FoundationItä-Suomen YliopistoCardiff UniversityGlaxoSmithKlineImperial College LondonUppsala UniversitetUniversity of WashingtonBrigham and Women's HospitalBritish Heart FoundationHarvard UniversityWellcome TrustUniversity of PennsylvaniaHáskóli ÍslandsUniversity of Bristol
KeywordsMeta-analysisCoronary heart diseaseMedicineInternal medicineCardiology

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)0.008
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.012
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.011
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0120.018
Bibliometrics0.0030.005
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.217
GPT teacher head0.399
Teacher spread0.182 · 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 designMeta-analysis
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

Citations824
Published2012
Admission routes1
Has abstractno

Explore more

Same venueThe LancetSame topicAdipokines, Inflammation, and Metabolic DiseasesFrench-language works237,207