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
Topic
Rough Sets and Fuzzy Logic
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.

939 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.
939 works in the cohort · of 4,299,418page 3 of 19

Labels cover 1 of 939 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 939 of 939 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
A rough sets based approach to feature selection
M. Zhang, JingTao Yao
2004· article· en· IEEE Annual Meeting of the Fuzzy Information, 2004. Processing NAFIPS '04.· Computer Science
machine prediction:candidate · noneconsensus · none
68
citations
affno abstractunlabeled
Web-Based Support Systems with Rough Set Analysis
JingTao Yao, Joseph P. Herbert
2007· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
65
citations
affno abstractunlabeled
Transactions on Rough Sets IV
James F. Peters, Andrzej Skowron
2005· book· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
63
citations
affunlabeled
Calculi of Approximation Spaces
Andrzej Skowron, Jarosław Stepaniuk, James F. Peters, Roman W. Świniarski
2006· article· en· Fundamenta Informaticae· Computer Science
machine prediction:candidate · noneconsensus · none
59
citations
affunlabeled
Rough clustering
Pawan Lingras, Georg Peters
2011· article· en· Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery· Computer Science
machine prediction:candidate · noneconsensus · none
51
citations
affno abstractunlabeled
Shadowed sets of dynamic fuzzy sets
Mingjie Cai, Qingguo Li, Guangming Lang
2016· article· en· Granular Computing· Computer Science
machine prediction:candidate · noneconsensus · none
51
citations
afffundno abstractunlabeled
Boosting of granular models
Witold Pedrycz, Keun Chang Kwak
2006· article· en· Fuzzy Sets and Systems· Computer Science
machine prediction:candidate · noneconsensus · none
49
citations
affno abstractunlabeled
A General Definition of an Attribute Reduct
Yan Zhao, Feng Luo, S. K. M. Wong, Yiyu Yao
2007· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
46
citations
affno abstractunlabeled
Fuzzy-Rough Cognitive Networks
Gonzalo Nápoles, Carlos Javier Mosquera, Rafael Falcón, Isel Grau, Rafael Bello, Koen Vanhoof
2017· article· en· Neural Networks· Computer Science
machine prediction:candidate · noneconsensus · none
44
citations
aboutno affunlabeled
Visualization and evolution of the scientific structure of fuzzy sets research in Spain
A.G. López‐Herrera, Manuel J. Cobo, Enrique Herrera‐Viedma, Francisco Herrera, Rafael Bailón‐Moreno, Evaristo Jiménez‐Contreras
2009· article· en· Institutional Repository of the University of Granada (University of Granada)· Computer Science
machine prediction:candidate · bibliometricsconsensus · none
44
citations
affunlabeled
Rough Neural Computing in Signal Analysis
J. F. Peters, L. Han, Sheela Ramanna
2001· article· en· Computational Intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
44
citations
affunlabeled
What ROC Curves Can't Do (and Cost Curves Can).
Chris Drummond, Robert C. Holte
2004· article· en· Diabetes Research and Clinical Practice· Computer Science
machine prediction:candidate · metaresearchconsensus · none
43
citations
affunlabeled
Human-Inspired Granular Computing
Yiyu Yao
2010· book-chapter· en· IGI Global eBooks· Computer Science
machine prediction:candidate · noneconsensus · none
43
citations

How this was built: Screen · Findings · About