MétaCan
Menu
Cohort builder

4,299,418 works, Canadian by any of four routes.

Every filter state is a URL; the URL is the query; the query is citable via /q/⟨hash⟩. The page, the API and the export parse the same parameters.

The current cohort, streamed from the database: every work column, the machine labels, the provisional scores, and the per-row validation status. Exports are capped at 100,000 rows. Mints a permanent /q/ link for this exact query. The same filters always produce the same link, whoever asks.

Search term
Author
Year range
Sort
Language
Type
Field
Venue
Nephrology Dialysis Transplantation
Topic
Retraction
Abstract
Evidence source
Study design
Label agreement
Label status

Direct Codex and Gemma labels are unvalidated and sparse. Distilled predictions cover the full frame and are also unvalidated. Choose the evidence source explicitly; absence of a direct label is never a negative label.

affaffiliation
fundfunder
venuejournal
aboutaboutness

The four routes compose: require the funder route and exclude affiliation to get the funder-only stratum no affiliation-based frame ever sees.

1,236 results · 1 filter active ·
Results by year
20002025
Publication date
Categories
Machine labels · sparse coverage
Evidence
Language
Type
Citations
An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
1,236 works in the cohort · of 4,299,418page 16 of 25

Labels cover 1 of 1,236 works in this cohort. The rest are unlabeled, which is not a negative label: the label table is sparse today and grows as labeling rounds land.

Distilled predictions cover 1,236 of 1,236 works in this cohort. Predictions are machine_predicted_unvalidated. The Gemma side is a direct model label for every work (title-only); the Codex side is a distilled, calibrated classifier. Candidate is the union; consensus is the intersection.

affunlabeled
The impact of acute kidney damage in the community
Javier Diaz, Laura Lidon, Inmaculada Saurí, Antonio Fernández, Maria V. Grau, José Luis Górriz +2 more
2024· article· en· Nephrology Dialysis Transplantation· Medicine
machine prediction:candidate · noneconsensus · none
1
citations
affunlabeled
Burden, access and disparities in kidney disease
Deidra C. Crews, Aminu K. Bello, Gamal Saadi, Philip Kam‐Tao Li, Guillermo García-García, Sharon Andreoli +4 more
2018· article· en· Nephrology Dialysis Transplantation· Medicine
machine prediction:candidate · noneconsensus · none
1
citations
affno abstractunlabeled
Reply
Sean M. Bagshaw, Carol George, Irina Dinu, Rinaldo Bellomo
2008· article· en· Nephrology Dialysis Transplantation· Medicine
machine prediction:candidate · noneconsensus · none
1
citations
affno abstractunlabeled
Reply
Marcello Tonelli
2008· article· en· Nephrology Dialysis Transplantation
machine prediction:candidate · insufficient_payloadconsensus · none
1
citations
affunlabeled
CKD GENERAL AND CLINICAL EPIDEMIOLOGY 2
Mogamat Razeen Davids, Nicola Marais, J. Jacobs, E Cohen, Irit Krause, Elad Goldberg +265 more
2014· article· en· Nephrology Dialysis Transplantation· Medicine
machine prediction:candidate · noneconsensus · none
1
citations
affunlabeled
Extracorporeal dialysis: techniques and adequacy
C. Donadio, A. Kanaki, Adoración Martín-Gómez, S. Garcia, M. Eugenia Palacios-Gómez, D. Calia +456 more
2012· article· en· Nephrology Dialysis Transplantation· Medicine
machine prediction:candidate · noneconsensus · none
1
citations
aboutno affunlabeled
P1584FRAILTY IN MAINTENANCE HEMODIALYSIS PATIENTS
Zauresh Amreyeva, Gulnar Chingayeva, Abay Shepetov, Assiya Kanatbayeva, Arina Yespotayeva
2020· article· en· Nephrology Dialysis Transplantation· Medicine
machine prediction:candidate · noneconsensus · none
1
citations
affunlabeled
Toxic acute renal failure
Kannaiyan S Rabindranath, Alison M. MacLeod, Norman Muirhead, Yang Kim, Kang Sun, Yeong Shik Kim +18 more
2006· article· en· Nephrology Dialysis Transplantation· Medicine
machine prediction:candidate · noneconsensus · none
1
citations

How this was built: Screen · Findings · About