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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.

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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Proceedings on Privacy Enhancing Technologies
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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.

78 results · 1 filter active ·
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20152025
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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.
78 works in the cohort · of 4,299,418page 2 of 2

Labels cover 0 of 78 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 78 of 78 works in this cohort. Predictions are machine_predicted_unvalidated teacher distillation outputs. Candidate is the union; consensus is the intersection.

aboutno affunlabeled
More and Scammier Ads: The Perils of YouTube's Ad Privacy Settings
Cat Mai, Bruno Coelho, Julia Kieserman, Lexie Matsumoto, Kyle Spinelli, Eric Yang +4 more
2025· article· en· Proceedings on Privacy Enhancing Technologies· Psychology
distilled prediction:candidate · metaepi_narrowconsensus · none
2
citations
affunlabeled
An Analysis of Chinese Censorship Bias in LLMs
Mohamed Serry, Jeffrey Knockel, Rachel Greenstadt
2025· article· en· Proceedings on Privacy Enhancing Technologies· Social Sciences
distilled prediction:candidate · noneconsensus · none
2
citations
afffundunlabeled
Private Multi-Winner Voting for Machine Learning
Adam Dziedzic, Christopher A. Choquette-Choo, Natalie Dullerud, Vinith Suriyakumar, Ali Shahin Shamsabadi, Muhammad Ahmad Kaleem +3 more
2023· article· en· Proceedings on Privacy Enhancing Technologies· Computer Science
distilled prediction:candidate · metaresearch+metaepi_narrow+open_scienceconsensus · open_science
1
citations
afffundunlabeled
Differentially Private Simple Genetic Algorithms
Thomas Humphries, Florian Kerschbaum
2023· article· en· Proceedings on Privacy Enhancing Technologies· Computer Science
distilled prediction:candidate · metaresearch+metaepi_narrow+open_scienceconsensus · open_science
1
citations
affunlabeled
Teaching an Old Dog New Tricks: Verifiable FHE Using Commodity Hardware
Jules Drean, Fisher Jepsen, G. Edward Suh, Srini Devadas, Aamer Jaleel, Gururaj Saileshwar
2025· article· en· Proceedings on Privacy Enhancing Technologies· Computer Science
distilled prediction:candidate · metaepi_narrow+scholarly_communicationconsensus · none
1
citations
affunlabeled
Automatic Generation of Web Censorship Probe Lists
Jenny Tang, Léo Alvarez, Arjun Brar, Nguyen Phong Hoang, Nicolas Christin
2024· article· en· Proceedings on Privacy Enhancing Technologies· Computer Science
distilled prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Editors’ Introduction
Florian Kerschbaum, Michelle L. Mazurek
2021· article· en· Proceedings on Privacy Enhancing Technologies· Computer Science
distilled prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Editors’ Introduction
Aaron Johnson, Florian Kerschbaum
2020· article· en· Proceedings on Privacy Enhancing Technologies· Social Sciences
distilled prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Editors’ Introduction
Aaron Johnson, Florian Kerschbaum
2021· article· en· Proceedings on Privacy Enhancing Technologies· Social Sciences
distilled prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Editors’ Introduction
Aaron Johnson, Florian Kerschbaum
2021· article· en· Proceedings on Privacy Enhancing Technologies· Social Sciences
distilled prediction:candidate · noneconsensus · none
0
citations
afffundunlabeled
Private Shared Random Minimum Spanning Forests
M. J. Dietz, Florian Kerschbaum
2025· article· en· Proceedings on Privacy Enhancing Technologies· Computer Science
distilled prediction:candidate · metaepi_narrowconsensus · none
0
citations

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