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Capacity for the management of kidney failure in the International Society of Nephrology Oceania and South East Asia (OSEA) region: report from the 2023 ISN Global Kidney Health Atlas (ISN-GKHA)
Anna Francis, Marina Wainstein, Georgina Irish, Muhammad Iqbal Abdul Hafidz, Titi Chen, Yeoungjee Cho, Htay Htay, Talerngsak Kanjanabuch, Rowena Lalji, Brendon L. Neuen, Emily See, Anim Md Shah, Brendan Smyth, Somkanya Tungsanga, Andrea K. Viecelli, Emily K. Yeung, 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, Muh Geot Wong, Sunita Bavanandan, Abdul Halim Abdul Gafor, Atefeh Amouzegar, Paul N. Bennett, Sonia L. Chicano, Mogamat Razeen Davids, Sara N. Davison, Hassane M. Diongole, Smita Divyaveer, Udeme E. Ekrikpo, Isabelle Éthier, Voon Ken Fong, Winston Wing‐Shing Fung, Anukul Ghimire, Gopal Basu, Hai An Ha Phan, David C.H. Harris, Ghenette Houston, Kwaifa Salihu Ibrahim, Meg Jardine, Kailash Jindal, Surasak Kantachuvesiri, Dearbhla Kelly, Peter G. Kerr, Siah Kim, Rathika Krishnasamy, Jia Liang Kwek, Vincent Lee, Adrian Liew, Chiao Yuen Lim, Aida Lydia, Aisha M. Nalado, Timothy O. Olanrewaju, Mohamed A. Osman, Анна Петрова, Khin Phyu Pyar, Parnian Riaz, Syed Saad, Aminu Muhammad Sakajiki, Noot Sengthavisouk, Stephen M. Sozio, Nattachai Srisawat, Eddie Tan, Sophanny Tiv, Isabelle Dominique Tomacruz Amante, A. R. Villanueva, Rachael Walker, Robert Walker, Deenaz Zaidi
Bibliographic record
VenueKidney International Supplements · 2024
Typearticle
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsUniversity of British ColumbiaUniversity of CalgaryUniversity of Alberta
FundersDaiichi Sankyo EuropeMedical Research CouncilChugai PharmaceuticalFaculty of Medicine and Health, University of SydneyJohns Hopkins Bloomberg School of Public HealthAkebia TherapeuticsFaculty of Medicine, Chulalongkorn UniversityPostgraduate Institute of Medical Education and Research, ChandigarhOtsuka PharmaceuticalFresenius Medical Care North AmericaAstellas PharmaFaculty of Medicine and Dentistry, University of AlbertaEli Lilly and CompanyChinese University of Hong KongUniversiteit StellenboschChulalongkorn UniversityAmgenGriffith UniversityBioCrystAustralian and New Zealand Society of NephrologyUniversity of AlbertaInternational Society of NephrologyAlexion PharmaceuticalsNational Research Council of ThailandKing Chulalongkorn Memorial HospitalIran University of Medical SciencesUniversiti Kebangsaan MalaysiaNational Health and Medical Research CouncilAstraZenecaUniversité de MontréalHeart and Stroke Foundation of CanadaJohns Hopkins University
KeywordsMedicinePopulationNephrologyKidney diseaseDialysisPeritoneal dialysisInternal medicineEnvironmental 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.
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)0.001
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 score0.873
Threshold uncertainty score0.727
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) | 0.001 | 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 head0.027
GPT teacher head0.300
Teacher spread0.273 · 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.
The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary
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
Citations7
Published2024
Admission routes2
Has abstractno