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Improving treatment decisions using personalized risk assessment from the International IgA Nephropathy Prediction Tool
Sean J. Barbour, Mark Canney, Rosanna Coppo, Hong Zhang, Yusuke Suzuki, Keiichi Matsuzaki, Ritsuko Katafuchi, Dilshani Induruwage, Lee Er, Heather N. Reich, John Feehally, Jonathan Barratt, Daniel Cattran, María Luisa Russo, S. Troyanov, H. Terence Cook, Ian S.D. Roberts, Vladimı́r Tesař, Dita Maixnerová, Sigrid Lundberg, Loreto Gesualdo, Francesco Emma, Laura Fuiano, G. Beltrame, Cristiana Rollino, A. Amore, Roberta Camilla, Licia Peruzzi, Manuel Praga, Sandro Feriozzi, Rosaria Polci, Giuseppe Segoloni, Loredana Colla, Antonello Pani, Doloretta Piras, Andrea Angioi, Giovanni Cancarini, S. Ravera, Magdalena Durlik, Elisabetta Moggia, José Ballarín, S. Di Giulio, Francesco Pugliese, I. Serriello, Mehmet Şükrü Sever, İşın Kiliçaslan, Francesco Locatelli, Lucia Del Vecchio, Jack F.M. Wetzels, Harm Peters, U. Berg, Fernanda Carvalho, A.C. da Costa Ferreira, M. Maggio, Andrzej Więcek, Mai Ots-Rosenberg, Riccardo Magistroni, Rezan Topaloğlu, Yelda Bilginer, Marco DʼAmico, Μaria Stangou, F Giacchino, Dimitrios Goumenos, Pantelitsa Kalliakmani, Miltiadis Gerolymos, Kres̆imir Gales̃ić, Colin Geddes, Kostas C. Siamopoulos, Olga Balafa, Marco Galliani, Piero Stratta, Marco Quaglia, R Bergia, Raffaella Cravero, Maurizio Salvadori, Lino Cirami, Bengt Fellström, Hilde Kloster Smerud, Franco Ferrario, T. Stellato, Jesús Egido, Carina Aguilar Martín, Jürgen Floege, Frank Eitner, Antonio Lupo, Patrizia Bernich, Paolo Mené, Massimo Morosetti, Cees van Kooten, Ton J. Rabelink, Marlies E. J. Reinders, J.M. Boria Grinyo, Stefano Cusinato, Luisa Benozzi, Silvana Savoldi, C. Licata, Małgorzata Mizerska-Wasiak, G Martina, A Messuerotti, Antonio Dal Canton, Ciro Esposito, C. Migotto, G Triolo, Filippo Mariano, Claudio Pozzi, R Boero, Shubha S. Bellur, Gianna Mazzucco, C. Giannakakis, E Honsová, B. Sundelin, Anna Maria Di Palma, Ester Gutiérrez, A.M. Asunis, Regina Tardanico, Agnieszka Perkowska‐Ptasińska, J. Arce Terroba, M. Fortunato, Afroditi Pantzaki, E. J. Steenbergen, Magnus Söderberg, Živile Riispere, Luciana Furci, Dıclehan Orhan, David Kipgen, Donatella Casartelli, Danica Galešić Ljubanović, Hariklia Gakiopoulou, E. Bertoni, Pablo Cannata Ortiz, Henryk Karkoszka, Hermann-Josef Groene, Antonella Stoppacciaro, Ingeborg M. Bajema, Jan A. Bruijn, Jadwiga Małdyk, E. Ioachim, Nüket Bavbek, Terry Cook, Charles E. Alpers, F. Berthoux, Stephen M. Bonsib, Vivette D. D’Agati, Giuseppe D’Amico, Steven N. Emancipator, F. Emmal, Fernando C. Fervenza, Sandrine Florquin, Agnes B. Fogo, Mark Haas, P. Hill, Ronald J. Hogg, Stephen I‐Hong Hsu, Tracy E. Hunley, Michelle Hladunewich, Caroline E. Jennette, Kensuke Joh, Bruce A. Julian, Tetsuya Kawamura, F M Lai, Chi Bon Leung, L. Li, P. Li, Zhihong Liu, Bruce Mackinnon, Sergio Mezzano, Francesco Paolo Schena, Yasuhiko Tomino, Patrick D. Walker, H. Wang, J J Weening, N. Yoshikawa N, Caihong Zeng, Sufang Shi, Chieko Nogi, Haruo Suzuki, Kentaro Koike, Keita Hirano, Takashi Yokoo, M. Hanai, Kei Fukami, Kazuo Takahashi, Y. Yuzawa, Misao Niwa, Yoshinari Yasuda, Shoji Maruyama, Daisuke Ichikawa, Takahide Suzuki, Sayuri Shirai, Akihisa Fukuda, Shota Fujimoto, Hernán Trimarchi
Bibliographic record
VenueKidney International · 2020
Typearticle
Languageen
FieldMedicine
TopicRenal Diseases and Glomerulopathies
Canadian institutionsUniversity of TorontoUniversity of British Columbia
FundersCanadian Institutes of Health Research
KeywordsImmunosuppressionMedicineProteinuriaNephropathyIntensive care medicineInternal medicineKidneyDiabetes mellitusEndocrinology
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.517
Threshold uncertainty score0.999
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 head0.034
GPT teacher head0.304
Teacher spread0.270 · 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 teacher head, not a consensus.
Study designObservational
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
Citations54
Published2020
Admission routes2
Has abstractno