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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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Privacy-Preserving Technologies in Data
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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.

1,809 results · 1 filter active ·
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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.
1,809 works in the cohort · of 4,299,418page 14 of 37

Labels cover 7 of 1,809 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 1,809 of 1,809 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
InfoClean
Fei Chiang, Dhruv Gairola
2017· article· en· Journal of Data and Information Quality· Computer Science
machine prediction:candidate · noneconsensus · none
9
citations
affunlabeled
Optimal and Differentially Private Data Acquisition
Alireza Fallah, Ali Makhdoumi, Azarakhsh Malekian, Asuman Ozdaglar
2022· article· en· Proceedings of the 23rd ACM Conference on Economics and Computation· Computer Science
machine prediction:candidate · noneconsensus · none
9
citations
affunlabeled
Cache Me If You Can
Miti Mazmudar, Thomas Humphries, Jiaxiang Liu, Matthew Rafuse, Xi He
2022· article· en· Proceedings of the VLDB Endowment· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · none
8
citations
affunlabeled
Machine Unlearning
Lucas Bourtoule, Varun Chandrasekaran, Christopher A. Choquette-Choo, Hengrui Jia, Adelin Travers, Baiwu Zhang +2 more
2019· preprint· en· arXiv (Cornell University)· Computer Science
machine prediction:candidate · noneconsensus · none
8
citations
affunlabeled
Don't be a tattle-tale
Primal Pappachan, Shufan Zhang, Xi He, Sharad Mehrotra
2022· article· en· Proceedings of the VLDB Endowment· Computer Science
machine prediction:candidate · noneconsensus · none
8
citations
affno abstractunlabeled
P4A: A New Privacy Model for XML
Angela Cristina Duta, Ken Barker
2008· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
8
citations
affunlabeled
Opinions of people
Anirban Basu, Jaideep Vaidya, Juan Camilo Corena, Shinsaku Kiyomoto, Stephen Marsh, Guibing Guo +2 more
2014· article· en· ACM SIGAPP Applied Computing Review· Computer Science
machine prediction:candidate · noneconsensus · none
8
citations
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