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Record W2130462669 · doi:10.1038/ng.2616

Dense genotyping of immune-related disease regions identifies nine new risk loci for primary sclerosing cholangitis

2013· review· en· W2130462669 on OpenAlexafffund
Jimmy Z. Liu, Johannes R. Hov, Trine Folseraas, Eva Ellinghaus, Simon Rushbrook, Nadezhda T. Doncheva, Ole A. Andreassen, Rinse K. Weersma, Tobias J. Weismüller, Bertus Eksteen, Pietro Invernizzi, Gideon M. Hirschfield, Daniel Gotthardt, Albert Parés, David Ellinghaus, Tejas Shah, Brian D. Juran, Piotr Milkiewicz, Christian Rust, Christoph Schramm, Tobias Müller, Brijesh Srivastava, Markus M. Nöthen, Stefan Herms, Juliane Winkelmann, Mitja Mitrovič, Felix Braun, Cyriel Y. Ponsioen, Peter J.P. Croucher, Martina Sterneck, Andreas Teufel, Andrew L. Mason, Janna Saarela, Virpi Leppä, Ruslan Dorfman, Domenico Alvaro, Annarosa Floreani, Suna Önengüt-Gümüşcü, Stephen S. Rich, Wesley K. Thompson, Andrew J. Schork, Sigrid Næss, Ingo Thomsen, Gabriele Mayr, Inke R. König, Kristian Hveem, Isabelle Cleynen, Javier Gutierrez‐Achury, Isis Ricaño-Ponce, David A. van Heel, Einar Björnsson, Richard Sandford, Peter R. Durie, Espen Melum, Morten H. Vatn, Mark S. Silverberg, Richard H. Duerr, Leonid Padyukov, Stephan Brand, Miquel Sans, Vito Annese, Jean–Paul Achkar, Kirsten Muri Boberg, Hanns–Ulrich Marschall, Olivier Chazouillères, Christopher L. Bowlus, Cisca Wijmenga, Erik Schrumpf, Séverine Vermeire, Mario Albrecht, John D. Rioux, Graeme Alexander, Annika Bergquist, Judy H. Cho, Stefan Schreiber, Michael P. Manns, Martti Färkkilâ, Anders M. Dale, Roger W. Chapman, Konstantinos N. Lazaridis, André Franke, Carl A. Anderson, Tom H. Karlsen

Bibliographic record

VenueNature Genetics · 2013
Typereview
Languageen
FieldMedicine
TopicLiver Diseases and Immunity
Canadian institutionsMontreal Heart InstituteMount Sinai HospitalHospital for Sick ChildrenUniversity of TorontoUniversité de MontréalUniversity of AlbertaUniversity of Calgary
FundersNational Center for Advancing Translational SciencesLerner Research Institute, Cleveland ClinicUniversity of California, DavisUniversité de ParisInstitut de Cardiologie de MontréalUniversitätsklinikum Hamburg-EppendorfAkershus UniversitetssykehusUniversity of ThessalyAssistance publique-Hôpitaux de ParisGraduate School of Public Health, University of PittsburghTerveyden ja hyvinvoinnin laitosRheinische Friedrich-Wilhelms-Universität BonnHospital for Sick ChildrenUniversity of California, San DiegoYale UniversityUniversity of TorontoMedizinischen Hochschule HannoverPomorski Uniwersytet Medyczny W SzczecinieUniversité de MontréalHelmholtz Zentrum MünchenSapienza Università di RomaUniversität zu LübeckKarolinska InstitutetCleveland ClinicRijksuniversiteit GroningenQueen Mary University of LondonNational Institute for Health and Care ResearchDeutsche ForschungsgemeinschaftHelsingin YliopistoUniversity of AlbertaUniversitat de BarcelonaNational Cancer InstituteLandspítali HáskólasjúkrahúsDepartment of Medicine, University of TorontoSahlgrenska AkademinUniversity of PittsburghTechnische Universität MünchenUniversitetet i OsloKU LeuvenUniversità degli Studi di PadovaNational Institute of Diabetes and Digestive and Kidney DiseasesBarts and The London School of Medicine and DentistryNorges Teknisk-Naturvitenskapelige UniversitetWellcome Trust
KeywordsBiologyPrimary sclerosing cholangitisGenotypingImmune systemDiseaseGeneticsPrimary (astronomy)ImmunologyGenotypeGeneInternal medicine

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.032
GPT teacher head0.311
Teacher spread0.279 · 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 designObservational
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

Citations398
Published2013
Admission routes2
Has abstractno

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