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Capacity for the management of kidney failure in the International Society of Nephrology South Asia region: report from the 2023 ISN Global Kidney Health Atlas (ISN-GKHA)
Eranga Wijewickrama, Muhammad Rafiqul Alam, Divya Bajpai, Smita Divyaveer, Arpana Iyengar, Vivek Kumar, Ahad Qayyum, Shankar Prasad Yadav, Manjusha Yadla, 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, Dibya Singh Shah, Narayan Prasad, Anil Agarwal, Ejaz Ahmed, Suceena Alexander, Atefeh Amouzegar, Urmila Anandh, Shyam Bihari Bansal, Pramod Kumar Chhetri, Yeoungjee Cho, Ugyen Choden, Nizamuddin Chowdury, Arvind Conjeevaram, Mogamat Razeen Davids, Sara N. Davison, Hassane M. Diongole, Udeme E. Ekrikpo, Isabelle Éthier, Edwin Fernando Mervin, Winston Wing‐Shing Fung, Reena Rachel George, Anukul Ghimire, Gopal Basu, Swarnalatha Guditi, Chula Herath, Ghenette Houston, Htay Htay, Kwaifa Salihu Ibrahim, Georgina Irish, Kailash Jindal, Ahmad Baseer Kaihan, Shubharthi Kar, Tasnuva Sarah Kashem, Dearbhla Kelly, Asia Khanam, Vijay Kher, Rowena Lalji, Sandeep Mahajan, Aisha M. Nalado, Rubina Naqvi, K.S. Nayak, Brendon L. Neuen, Timothy O. Olanrewaju, Mohamed A. Osman, Sreejith Parameswaran, Klara Paudel, Анна Петрова, Harun Ur Rashid, Parnian Riaz, Syed Saad, Manisha Sahay, Aminu Muhammad Sakajiki, Emily See, Mythri Shankar, Ajay P. Sharma, Sourabh Sharma, Ibrahim Shiham, Geetika Singh, Stephen M. Sozio, Sophanny Tiv, Mayuri Trivedi, Somkanya Tungsanga, Andrea K. Viecelli, Marina Wainstein, Abdul Wazil, Dilushi Wijayaratne, Emily K. Yeung, Deenaz Zaidi
Bibliographic record
VenueKidney International Supplements · 2024
Typereview
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsUniversity of British ColumbiaUniversity of CalgaryUniversity of Alberta
FundersSchulich School of Medicine and DentistryFaculty of Medicine, Chulalongkorn UniversityCanadian Institutes of Health ResearchJohns Hopkins Bloomberg School of Public HealthGeorge Institute for Global HealthUniversity of ColomboAlberta InnovatesChulalongkorn UniversityUniversity of AlbertaInternational Society of NephrologyMcMaster UniversityLondon Health Sciences CentreJohns Hopkins UniversityPfizerFaculty of Medicine and Dentistry, University of AlbertaAstraZenecaAlberta Health ServicesUniversity of OttawaSchulich School of Medicine and Dentistry, Western UniversityUniversiteit UtrechtSanofiAlexion Pharmaceuticals
KeywordsKidney diseaseMedicineNephrologyPublic healthHealth carePeritoneal dialysisGlobal healthEnvironmental healthIntensive care medicineEconomic growthInternal medicineNursing
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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.625
Threshold uncertainty score1.000
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| 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 head0.056
GPT teacher head0.359
Teacher spread0.303 · 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 designNot applicable
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
Citations13
Published2024
Admission routes2
Has abstractno