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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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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.

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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.

1,256 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.
1,256 works in the cohort · of 4,299,418page 6 of 26

Labels cover 2 of 1,256 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 1,256 of 1,256 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
On pruning for top-k ranking in uncertain databases
Chonghai Wang, Li Yan Yuan, Jia-Huai You, Osmar R. Zai͏̈ane, Jian Pei
2011· article· en· Proceedings of the VLDB Endowment· Computer Science
machine prediction:candidate · noneconsensus · none
17
citations
affno abstractunlabeled
Indexing Reverse Top-k Queries in Two Dimensions
Sean Chester, Alex Thomo, Sue Whitesides
2013· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
17
citations
affunlabeled
E-Tourism: Mobile Dynamic Trip Planner
Hamzah Alghamdi, Shiai Zhu, Abdulmotaleb El Saddik
2016· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
16
citations
affunlabeled
A topological sorting algorithm for large graphs
Deepak Ajwani, Adan Cosgaya-Lozano, Norbert Zeh
2012· article· en· ACM Journal of Experimental Algorithmics· Computer Science
machine prediction:candidate · noneconsensus · none
16
citations
affunlabeled
Distributed Stream KNN Join
Amirhesam Shahvarani, Hans‐Arno Jacobsen
2021· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
16
citations
affunlabeled
Group-Based Skyline for Pareto Optimal Groups
Jinfei Liu, Li Xiong, Jian Pei, Jun Luo, Haoyu Zhang, Wenhui Yu
2019· article· en· IEEE Transactions on Knowledge and Data Engineering· Computer Science
machine prediction:candidate · noneconsensus · none
16
citations
affno abstractunlabeled
Answering Queries Using Views
Vasilis Vassalos
2009· book-chapter· en· Encyclopedia of Database Systems· Computer Science
machine prediction:candidate · noneconsensus · none
16
citations
affunlabeled
Surveying the landscape
Bogdan Simion, Suprio Ray, Angela Demke Brown
2012· article· en· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · none
15
citations
affno abstractunlabeled
(Approximate) Uncertain Skylines
Peyman Afshani, Pankaj K. Agarwal, Lars Arge, Kasper Green Larsen, Jeff M. Phillips
2012· article· en· Theory of Computing Systems· Computer Science
machine prediction:candidate · noneconsensus · none
15
citations
affno abstractunlabeled
Query Expansion for Information Retrieval
Olga Vechtomova
2017· book-chapter· en· Encyclopedia of Database Systems· Computer Science
machine prediction:candidate · noneconsensus · none
15
citations
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