MétaCan
Menu
Back to cohort
Record W4394580193 · doi:10.1016/j.kisu.2024.01.009

Capacity for the management of kidney failure in the International Society of Nephrology Middle East region: report from the 2023 ISN Global Kidney Health Atlas (ISN-GKHA)

2024· article· en· W4394580193 on OpenAlexafffund
Sabine Karam, Atefeh Amouzegar, Iman Alshamsi, Saeed M.G. Al Ghamdi, Siddiq Anwar, Mohammad Ghnaimat, Bassam Saeed, 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, Ali K. Abu‐Alfa, Shokoufeh Savaj, Pauline Abou-Jaoudeh, Turki Al Hussain, Issa Al Salmi, Mona Alrukhaimi, Anas Alyousef, Sola Aoun Bahous, Guangyan Cai, Hicham I. Cheikh Hassan, Yeoungjee Cho, Mogamat Razeen Davids, Sara N. Davison, Hassane M. Diongole, Smita Divyaveer, Udeme E. Ekrikpo, Isabelle Éthier, Winston Wing‐Shing Fung, Anukul Ghimire, Nakysa Hooman, Ghenette Houston, Htay Htay, Kwaifa Salihu Ibrahim, Georgina Irish, Kailash Jindal, Dearbhla Kelly, Rowena Lalji, Ahmed Mitwali, Mojgan Mortazavi, Aisha M. Nalado, Brendon L. Neuen, Timothy O. Olanrewaju, Mohamed A. Osman, Shahrzad Ossareh, Анна Петрова, Parnian Riaz, Syed Saad, Aminu Muhammad Sakajiki, Emily See, Stephen M. Sozio, Sophanny Tiv, Somkanya Tungsanga, Andrea K. Viecelli, Marina Wainstein, Hala Wannous, Emily K. Yeung, 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
FundersFaculty of Medicine and Dentistry, University of AlbertaJohns Hopkins Bloomberg School of Public HealthGeorge Institute for Global HealthNile UniversityUniversité de MontréalChinese University of Hong KongIsfahan University of Medical SciencesFaculty of Health and Medical Sciences, University of Western AustraliaUniversity of OxfordInternational Society of NephrologyUniversity of AlbertaUniversiteit UtrechtIran University of Medical SciencesDuke-NUS Medical SchoolRoyal Adelaide HospitalUniversity of OttawaSingapore General HospitalMcMaster UniversityJohns Hopkins University
KeywordsMedicineKidney diseaseNephrologyKidney transplantationDialysisTransplantationPeritoneal dialysisInternal medicineHemodialysisPublic healthIntensive care medicineEnvironmental healthPathology

Abstract

fetched live from OpenAlex
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 imitation

Not 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)0.007
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.128
Threshold uncertainty score0.255

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.013
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.004
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0080.002

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 head0.044
GPT teacher head0.310
Teacher spread0.266 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine 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 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

Citations12
Published2024
Admission routes2
Has abstractno

Explore more

Same venueKidney International SupplementsSame topicDialysis and Renal Disease ManagementFrench-language works237,207