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Experimental models of CKD
Rattiyaporn Kanlaya, Kitisak Sintiprungrat, Visith Thongboonkerd, N. Torremade, René J.M. Bindels, Joost G.J. Hoenderop, E. Fernandez, Adriana Dusso, José Manuel Valdivielso, T. Krueger, Peter Boor, Christopher A. Schafer, Ralf Westenfeld, V. Brandenburg, Georg Schlieper, Willi Jahnen‐Dechent, Markus Ketteler, W.S.S. Jee, X. Li, B. Richards, J. Floege, J. G. Goncalves, D. Canale, Ana Carolina de Bragança, Motohiro Shimizu, Rosa Maria Affonso Moysés, Lúcia Andrade, A. C. Seguro, R. A. Volpini, S. Romoli, A. Migliorini, H.-J. Anders, O. Eskova, Natalia Neprintseva, N. Tchebotareva, I. Bobkova, Lidia Kozlovskaya, I. Simic, Mansoureh Tabatabaeifar, Tanja Wlodkowski, Helga Denc, Géraldine Mollet, Corinne Antignac, F. Schaefer, Ivanova A Ekaterina, Luciana Giardino, M. P. Rastaldi, Lambertus P. van den Heuvel, Elena Levtchenko, Chikako Okina, T. Okamoto, Masakazu Kamata, Junya Murano, Koichi S. Kobayashi, Kazuhiko Takeuchi, F. Kamata, Takashi Sakai, Shiho Naito, Tatsuo Aoyama, Takanori Sano, Yusuke Leo Takeuchi, K. Kamata, Dana Thomasová, Helge Bruns, H. Liapis, T. Iwashita, H. Hasegawa, K. Takayanagi, Takeshi Shimizu, J. Asakura, S. Okazaki, Yuta Kogure, Minoru Hatano, H. Hara, M. Inamura, Mizuki Iwanaga, Toshifumi Mitani, Tetsuya Mitarai, V. J. Savin, Madhav Sharma, Changli Wei, Jochen Reiser, Ellen T. McCarthy, Raj Kumar Sharma, J.-F. Gauchat, Benedicte Eneman, Kathleen Freson, Chris Van Geet, D. E. Choi, Jin Young Jeong, Y. K. Chang, K.-R. Na, K. W. Lee, Y. T. Shin, Haifeng Ni, Jiang‐Fan Chen, Minghui Zhang, Mingming Pan, B.-C. Liu, S. S. Kim, Taihei Suzuki, M. Iyoda, Kaoru Matsumoto, Y. Shindo-Hirai, Yoshinori Kuno, Yukihiro Wada, Yoshino Yamamoto, Takanori Shibata, T. Akizawa, J. M. Munoz-Felix, José M. López‐Novoa, Josef Ehling, Janka Bábíčková, Felix Gremse, Fabian Kießling, Twan Lammers, M. Lech, R. Gunthner, G. Lorenz, Michelle Ryu, R. Grobmayr, H. Susanti, Richard A. Flavell, Sandra Rayego‐Mateos, J. Morgado, Ana B. Sanz, Satoru Eguchi, János Pató, Gÿorgý Kéri, J. Egido, Alberto Ortíz, M. Ruiz-Ortega, Marion Leduc, Lilianne Geerts, Brigitte Grouix, François Sarra‐Bournet, A. Felton, Lisa Gervais, Shaun Abbott, Jean‐Simon Duceppe, Boulos Zacharie, Pia Laurin, Lyne Gagnon, Maria G. Detsika, Pu Duann, Elias A. Lianos, K. I. Leong, C.-K. Chiang, Chih‐Chao Yang, Chiao‐En Wu, Liping Chen, K.-Y. Hung, Shing‐Hwa Liu, F. F. Carvalho, V. P. Teixeira, W. S. Almeida, N. Schor, David M. Small, Nigel C. Bennett, Jeff S. Coombes, David W. Johnson, G. Gobe, Núria Montero, A.G. Prada, Marta Riera, M. Orfila, Julio Pascual, E. Rodríguez, Carlos H. Barrios, G. Kokeny, Krisztina Fazekas, L. Rosivall, M. M. Mozes, Nick Hornigold, Jeremy Hughes, Andrew Mooney, Agnès Bénardeau, William Riboulet, Anthony Vandjour, B. Jacobsen, Christian Apfel, Karin Conde‐Knape, Liette Gervais, Jean-François Bienvenu, T. Tanaka, J. Yamaguchi, M. Nangaku, Toshimitsu Niwa, D. Bolati, Hirotaka Shimizu, M. Yisireyili, F. Nishijima, Alessandra Brocca, Grazia Maria Virzì, Massimo de Cal, Claudio Ronco, G. Priante, E. Musacchio, C. Valvason, Leonardo Sartori, Antonio Piccoli, B. Baggio, Michael Perkuhn, Martin Weibrecht, S. Zok, I. V. Martin, Felix Schoth, Tammo Ostendorf, Christiane Kühl, А. Ж. Карабаева, A. Essaian, O. Beresneva, M. Parastaeva, I. G. Kayukov, А. В. Смирнов, Irena Audzeyenka, Małgorzata Kasztan, Agnieszka Piwkowska, Dorota Rogacka, S Angielski, M. Jankowski, Clemens L. Bockmeyer, K. Kokowicz, P. A. Agustian, S. Zell, J. Wittig, Jan U. Becker, Ryuzoh Nishizono, Madhusudan Venkatareddy, M. A. H. Chowdhury, S. Q. Wang, Akiko Fukuda, Larysa Wickman, Yan Yang, Roger C. Wiggins, M. R. Fazio, V. Donato, S. Lucisano, V. Cernaro, R. Lupica, D. Trimboli, Gaetano Montalto, C. Aloisi, Anna Mazzeo, M. Buemi, Olga Gawryś, Krzysztof H. Olszyński, Marta Kuczeriszka, K. Gawarecka, Ewa Świeżewska, Marek Chmielewski, Marek Masnyk, J Rafałowska, Elżbieta Kompanowska‐Jezierska, W.-C. Lee, Y.-Y. Chau, L.-C. Lee, Chun-Hsiang Chiu, C.-T. Lee, J.-B. Chen, S. J. Shin
Bibliographic record
VenueNephrology Dialysis Transplantation · 2013
Typearticle
Languageen
FieldMedicine
TopicElectrolyte and hormonal disorders
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsMedicineKidney diseaseIntensive care medicineInternal medicine
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 machine prediction
Teacher imitationNot 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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.033
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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 head0.012
GPT teacher head0.251
Teacher spread0.239 · 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 source (direct Gemma or distilled Codex), not a consensus.
The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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
Citations0
Published2013
Admission routes1
Has abstractno