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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.

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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.

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Rough Sets and Fuzzy Logic
Retraction
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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
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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 ·
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20002025
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Machine labels · sparse coverage
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An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
939 works in the cohort · of 4,299,418page 2 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.

affno abstractunlabeled
The Art of Granular Computing
Yiyu Yao
2007· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
136
citations
afffundno abstractunlabeled
Rough Sets and Bayes Factor
Dominik Ślȩzak
2005· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
120
citations
affno abstractunlabeled
Foundations of near sets
James F. Peters, Piotr Wasilewski
2009· article· en· Information Sciences· Computer Science
machine prediction:candidate · noneconsensus · none
113
citations
affno abstractunlabeled
Naive Bayesian Rough Sets
Yiyu Yao, Bing Zhou
2010· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
105
citations
afffundno abstractunlabeled
Ensemble selector for attribute reduction
Xibei Yang, Yiyu Yao
2018· article· en· Applied Soft Computing· Computer Science
machine prediction:candidate · noneconsensus · none
103
citations
affunlabeled
Granular Computing Using Information Tables
Yiyu Yao, Ning Zhong
2002· book-chapter· en· Studies in fuzziness and soft computing· Computer Science
machine prediction:candidate · noneconsensus · none
100
citations
fundno affno abstractunlabeled
Dominance-based rough set approach for group decisions
Salem Chakhar, Alessio Ishizaka, Ashraf Labib, Inès Saad
2015· article· en· European Journal of Operational Research· Computer Science
machine prediction:candidate · noneconsensus · none
96
citations
affunlabeled
On the System Algebra Foundations for Granular Computing
Yingxu Wang, Lotfi A. Zadeh, Yiyu Yao
2009· article· en· International Journal of Software Science and Computational Intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
92
citations
affunlabeled
Abstraction and specialization of information granules
Witold Pedrycz, George Vukovich
2001· article· en· IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)· Computer Science
machine prediction:candidate · noneconsensus · none
88
citations
affno abstractunlabeled
Relational concept discovery in structured datasets
Marianne Huchard, Mohamed Rouane Hacene, Clément Roume, Petko Valtchev
2007· article· en· Annals of Mathematics and Artificial Intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
86
citations
afffundunlabeled
Rough set approximations in formal concept analysis
Yiyu Yao, Yaohua Chen
2004· article· en· IEEE Annual Meeting of the Fuzzy Information, 2004. Processing NAFIPS '04.· Computer Science
machine prediction:candidate · noneconsensus · none
80
citations
affunlabeled
From Annotator Agreement to Noise Models
Beata Beigman Klebanov, Eyal Beigman
2009· article· en· Computational Linguistics· Computer Science
machine prediction:candidate · metaresearchconsensus · none
77
citations
affno abstractunlabeled
Transactions on Rough Sets IX
James F. Peters
2008· book· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
75
citations
afffundno abstractunlabeled
Criteria for choosing a rough set model
Joseph P. Herbert, JingTao Yao
2008· article· en· Computers & Mathematics with Applications· Computer Science
machine prediction:candidate · noneconsensus · none
74
citations
affunlabeled
Granular Mappings
A Bargiela, Witold Pedrycz
2005· article· en· IEEE Transactions on Systems Man and Cybernetics - Part A Systems and Humans· Computer Science
machine prediction:candidate · noneconsensus · none
70
citations
affunlabeled
Data Mining Based on Rough Sets
Jerzy W. Grzymala‐Busse, Wojciech Ziarko
2003· book-chapter· en· IGI Global eBooks· Computer Science
machine prediction:candidate · noneconsensus · none
68
citations
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