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Capacity for the management of kidney failure in the International Society of Nephrology Western Europe region: report from the 2023 ISN Global Kidney Health Atlas (ISN-GKHA)
Maria Pippias, Gaetano Alfano, Dearbhla Kelly, María José Soler, Letizia De Chiara, Timothy O. Olanrewaju, Silvia Arruebo, Aminu K. Bello, Fergus Caskey, Sandrine Damster, Jo‐Ann Donner, Vivekanand Jha, David W. Johnson, Adeera Levin, Charu Malik, Masaomi Nangaku, Ikechi G. Okpechi, Marcello Tonelli, Feng Ye, Rosanna Coppo, Liz Lightstone, Atefeh Amouzegar, Hans‐Joachim Anders, Jyoti Baharani, Debasish Banerjee, Boris Bikbov, Edwina A. Brown, Yeoungjee Cho, Kathleen Claes, Naomi Clyne, Mogamat Razeen Davids, Sara N. Davison, Hassane M. Diongole, Smita Divyaveer, Gavin Dreyer, Jan Dudley, Udeme E. Ekrikpo, Isabelle Éthier, Rhys Evans, Stanley Fan, Winston Wing‐Shing Fung, Maurizio Gallieni, Anukul Ghimire, Ghenette Houston, Htay Htay, Kwaifa Salihu Ibrahim, Georgina Irish, Kailash Jindal, Arif Khwaja, Rowena Lalji, Vassilios Liakopoulos, Valérie A. Luyckx, Hans‐Peter Marti, Piergiorgio Messa, Thomas Müller, Aisha M. Nalado, Brendon L. Neuen, Dorothea Nitsch, Fernando Nolasco, Rainer Oberbauer, Mohamed A. Osman, Αikaterini Papagianni, Анна Петрова, Giorgina Barbara Piccoli, Liam Plant, Giuseppe Remuzzi, Parnian Riaz, Joris J. T. H. Roelofs, Michael A. Rudnicki, Syed Saad, Aminu Muhammad Sakajiki, Johannes B. Scheppach, Emily See, Rukshana Shroff, Marit D. Solbu, Stephen M. Sozio, Giovanni FM Strippoli, Maarten W. Taal, James Tataw Ashu, Sophanny Tiv, Somkanya Tungsanga, Jeroen B. van der Net, Raymond Vanholder, Andrea K. Viecelli, Katie Vinen, Bruno Vogt, Marina Wainstein, Talia Weinstein, David C. Wheeler, Emily K. Yeung, Deenaz Zaidi
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
Bibliographic record
VenueKidney International Supplements · 2024
Typearticle
Languageen
FieldMedicine
TopicRenal and Vascular Pathologies
Canadian institutionsUniversity of British ColumbiaUniversity of CalgaryUniversity of Alberta
FundersBarts Health NHS TrustSkånes universitetssjukhusHaukeland UniversitetssjukehusUniversity of Cape TownAristotle University of ThessalonikiUniversité de MontréalFaculty of Medicine and Dentistry, University of AlbertaChinese University of Hong KongBrigham and Women's HospitalUniversiteit StellenboschDuke-NUS Medical SchoolKU LeuvenUniversität WienUniversidade Nova de LisboaMedizinische Universität WienPostgraduate Institute of Medical Education and Research, ChandigarhGeorge Institute for Global HealthUniversity College LondonInternational Society of NephrologyUniversity of AlbertaLunds UniversitetIstituto di Ricerche Farmacologiche Mario Negri - IRCCSUniversität ZürichNile UniversityFaculty of Health and Medical Sciences, University of Western AustraliaRoyal Adelaide HospitalSingapore General HospitalMcMaster UniversityUniversity of OttawaUniversitetet i BergenUniversity College Cork
KeywordsKidney diseaseMedicineNephrologyWorkforceDialysisKidney transplantationPeritoneal dialysisHealth careRenal replacement therapyPopulationGovernment (linguistics)Intensive care medicineTransplantationInternal medicineEconomic growthEnvironmental health
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.
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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Commentary · Consensus signal: none
Teacher disagreement score0.633
Threshold uncertainty score0.476
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 head0.045
GPT teacher head0.331
Teacher spread0.286 · 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 itQuick stats
Citations12
Published2024
Admission routes2
Has abstractno