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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
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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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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 ·
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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 19 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
Triangular Norms
Vilém Novák
2009· book-chapter· en· Encyclopedia of Database Systems· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
City Indicators : Now to Nanjing
Daniel Hoornweg, Fernanda Ruiz Nuñez, Mila Freire, Natalie Palugyai, Maria Villaveces, Eduardo Wills-Herrera
2012· article· en· RePEc: Research Papers in Economics· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Optimizing Rough Set Flow Graph Inference
Jun Wang, Cory J. Butz
2024· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
afffundno abstractunlabeled
On some generalization of rough sets
Ryszard Janicki
2023· article· en· International Journal of Approximate Reasoning· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Towards the Definition of Spatial Granules
Liquan Zhao, Yiyu Yao
2023· preprint· en· SSRN Electronic Journal· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Logic-Based Fuzzy Clustering
Andrzej Bargieła, Witold Pedrycz
2003· book-chapter· en· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
fundno affunlabeled
On Data Manifolds Entailed by Structural Causal Models
Ricardo Dominguez-Olmedo, Amir-Hossein Karimi, Georgios Arvanitidis, Bernhard Schölkopf
2023· article· en· Technical University of Denmark, DTU Orbit (Technical University of Denmark, DTU)· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Granular Approximations of Partially-Known Concepts
Qiaoyi Li, Chengjun Shi, Han Yang, Yiyu Yao
2024· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Variable Precision Approximations of Rough Sets
Wojciech Ziarko
2023· book-chapter· en· Encyclopedia of complexity and systems science series· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
[no title]
2023· other· en· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affno abstractunlabeled
Rough Sets
Andrzej Bargieła, Witold Pedrycz
2003· book-chapter· en· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
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