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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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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.
1,809 works in the cohort · of 4,299,418page 33 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.

fundno affunlabeled
Robust and Efficient Collaborative Learning
Abdellah El Mrini, Sadegh Farhadkhan, Rachid Guerraoui
2025· preprint· en· ArXiv.org· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Dataveillance
2014· book-chapter· en· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Summary and Future Research Directions
Kuan Zhang, Xuemin Shen
2015· book-chapter· en· Wireless networks· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Planet Sculptures and Chair Sculptures
2021· article· en· UND Scholarly Commons (University of North Dakota)· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affunlabeled
Private Boosted Decision Trees via Smooth Re-Weighting
Mohammadmahdi Jahanara, Vahid R. Asadi, Marco Carmosino, Akbar Rafiey, Bahar Salamatian
2023· article· en· Journal of Privacy and Confidentiality· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
afffundunlabeled
A Bias-Accuracy-Privacy Trilemma for Statistical Estimation
Gautam Kamath, Argyris Mouzakis, Matthew Regehr, Vikrant Singhal, Thomas Steinke, Jonathan Ullman
2024· article· en· Journal of the American Statistical Association· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Related Work
Wen Ming Liu, Lingyu Wang
2016· book-chapter· en· Advances in information security· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affno abstractunlabeled
Privacy-Preserving Health Data Processing
Kuan Zhang, Xuemin Shen
2015· book-chapter· en· Wireless networks· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Back to School (Complete Anonymized Data)
Blake Lee‐Whiting, Thomas Bergeron
2023· dataset· en· Harvard Dataverse· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Online Privacy Heuristics
Reda Alhajj, Jon Rokne
2018· book-chapter· en· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Privacy in Location-Based Services: Present Facts and Future Paths
Zakaria Sahnoune, Esma Aı̈meur
2019· book-chapter· en· Lecture notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
P2NIA: Privacy-Preserving Non-iterative Auditing
Jade Garcia Bourrée, Hadrien Lautraite, Sébastien Gambs, Gilles Trédan, Erwan Le Merrer, Benoît Rottembourg
2025· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
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