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Gout, Hyperuricaemia and Crystal-Associated Disease Network (G-CAN) consensus statement regarding labels and definitions of disease states of gout

2019· article· en· W2972414225 on OpenAlexaff
David Bursill, William J. Taylor, Robert Terkeltaub, Abhishek Abhishek, Alexander So, Ana Beatriz Vargas‐Santos, Angelo Gaffo, Ann K. Rosenthal, Anne-Kathrin Tausche, Anthony M. Reginato, Bernhard Manger, Carlo Alberto Scirè, Carlos Pineda, Caroline van Durme, Ching-Tsai Lin, Congcong Yin, Daniel Albert, Edyta Biernat‐Kałuża, Edward Roddy, Eliseo Pascual, Fabio Becce, Fernando Pérez-Ruiz, Francisca Sivera, Frédéric Lioté, Georg Schett, George Nuki, Georgios Filippou, Géraldine McCarthy, Geraldo da Rocha Castelar Pinheiro, Hang‐Korng Ea, Helena de Almeida Tupinambá, Hisashi Yamanaka, Hyon K. Choi, James Mackay, James R. O’Dell, Janitzia Vázquez Mellado, Jasvinder A. Singh, John FitzGerald, L. Jacobsson, Leo A. B. Joosten, Leslie R. Harrold, Lisa K. Stamp, Mariano Andrés, Marwin Gutiérrez, Masanari Kuwabara, Mats Dehlin, M. Janssen, Michael Doherty, Michael S. Hershfield, Michael H. Pillinger, N. Lawrence Edwards, Naomi Schlesinger, Nitin Kumar, Ole Slot, Sébastien Ottaviani, Pascal Richette, Paul MacMullan, Peter T. Chapman, Peter E. Lipsky, Philip C. Robinson, Puja Khanna, Rada Gancheva, Rebecca Grainger, Richard J. Johnson, Ritch te Kampe, Robert T. Keenan, Sara K. Tedeschi, Seoyoung C. Kim, Sung Jae Choi, Theodore Fields, Thomas Bardin, Till Uhlig, Tim Jansen, Tony R. Merriman, Tristan Pascart, Tuhina Neogi, Viola Klück, Worawit Louthrenoo, Nicola Dalbeth

Bibliographic record

VenueAnnals of the Rheumatic Diseases · 2019
Typearticle
Languageen
FieldMedicine
TopicGout, Hyperuricemia, Uric Acid
Canadian institutionsUniversity of Calgary
FundersNational Institute of Arthritis and Musculoskeletal and Skin DiseasesU.S. Department of Veterans Affairs
KeywordsGoutMedicineTophusHyperuricemiaAsymptomaticInternal medicineRheumatologyDiseasePhysical therapyUric acid

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)0.055
metaresearch head score (Gemma)0.080
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.058
Threshold uncertainty score0.290

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0550.080
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.009
Bibliometrics0.0090.008
Science and technology studies0.0040.004
Scholarly communication0.0060.003
Open science0.0080.007
Research integrity0.0090.015
Insufficient payload (model declined to judge)0.0040.002

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 head0.038
GPT teacher head0.274
Teacher spread0.236 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations119
Published2019
Admission routes1
Has abstractno

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