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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 1 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. 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
Privacy-preserving Machine Learning as a Service
Ehsan Hesamifard, Hassan Takabi, Mehdi Ghasemi, Rebecca N. Wright
2018· article· en· Proceedings on Privacy Enhancing Technologies· Computer Science
machine prediction:candidate · noneconsensus · none
255
citations
aboutno affunlabeled
Privacy Attitudes of Smart Speaker Users
Nathan Malkin, Joe Deatrick, Allen Tong, Primal Wijesekera, Serge Egelman, David Wagner
2019· article· en· Proceedings on Privacy Enhancing Technologies· Social Sciences
machine prediction:candidate · noneconsensus · none
168
citations
afffundunlabeled
DP5: A Private Presence Service
Nikita Borisov, George Danezis, Ian Goldberg
2015· article· en· Proceedings on Privacy Enhancing Technologies· Computer Science
machine prediction:candidate · noneconsensus · none
65
citations
afffundunlabeled
SoK: Making Sense of Censorship Resistance Systems
Sheharbano Khattak, Tariq Elahi, Laurent Simon, Colleen M. Swanson, Steven J. Murdoch, Ian Goldberg
2016· article· en· Proceedings on Privacy Enhancing Technologies· Computer Science
machine prediction:candidate · noneconsensus · none
54
citations
affunlabeled
On the Privacy Implications of Location Semantics
Berker Ağır, Kévin Huguenin, Urs Hengartner, Jean‐Pierre Hubaux
2016· article· en· Proceedings on Privacy Enhancing Technologies· Computer Science
machine prediction:candidate · noneconsensus · none
43
citations
afffundunlabeled
Lower-Cost ∈-Private Information Retrieval
Raphael R. Toledo, George Danezis, Ian Goldberg
2016· article· en· Proceedings on Privacy Enhancing Technologies· Computer Science
machine prediction:candidate · noneconsensus · none
42
citations
affunlabeled
The Price is (Not) Right: Comparing Privacy in Free and Paid Apps
Catherine Han, Irwin Reyes, Álvaro Feal, Joel Reardon, Primal Wijesekera, Narseo Vallina-Rodríguez +3 more
2020· article· en· Proceedings on Privacy Enhancing Technologies· Computer Science
machine prediction:candidate · noneconsensus · none
36
citations
affunlabeled
Privacy-preserving Wi-Fi Analytics
Mohammad Alaggan, Mathieu Cunche, Sébastien Gambs
2018· article· en· Proceedings on Privacy Enhancing Technologies· Computer Science
machine prediction:candidate · noneconsensus · none
34
citations
affunlabeled
Efficient Server-Aided 2PC for Mobile Phones
Payman Mohassel, Ostap Orobets, Ben Riva
2015· article· en· Proceedings on Privacy Enhancing Technologies· Computer Science
machine prediction:candidate · noneconsensus · none
28
citations
afffundunlabeled
Differentially Private Speaker Anonymization
Ali Shahin Shamsabadi, Brij Mohan Lal Srivastava, Aurélien Bellet, Nathalie Vauquier, Emmanuel Vincent, Mohamed Maouche +2 more
2023· article· en· Proceedings on Privacy Enhancing Technologies· Computer Science
machine prediction:candidate · noneconsensus · none
27
citations
affunlabeled
Disparate Vulnerability to Membership Inference Attacks
Bogdan Kulynych, Mohammad Yaghini, Giovanni Cherubin, Michael Veale, Carmela Troncoso
2021· preprint· en· Proceedings on Privacy Enhancing Technologies· Computer Science
machine prediction:candidate · noneconsensus · none
18
citations
affunlabeled
SoK: Privacy-Preserving Reputation Systems
Stan Gurtler, Ian Goldberg
2020· article· en· Proceedings on Privacy Enhancing Technologies· Computer Science
machine prediction:candidate · noneconsensus · none
14
citations
affunlabeled
A Bit More Than a Bit Is More Than a Bit Better
Syed Mahbub Hafiz, Ryan Henry
2019· article· en· Proceedings on Privacy Enhancing Technologies· Computer Science
machine prediction:candidate · noneconsensus · none
11
citations
afffundunlabeled
SoK: Metadata-Protecting Communication Systems
Sajin Sasy, Ian Goldberg
2023· article· en· Proceedings on Privacy Enhancing Technologies· Computer Science
machine prediction:candidate · noneconsensus · none
10
citations
fundno affunlabeled
Trace Oddity: Methodologies for Data-Driven Traffic Analysis on Tor
Vera Rimmer, Theodor Schnitzler, Tom Van Goethem, Abel Rodríguez Romero, Wouter Joosen, Katharina Kohls
2022· article· en· Proceedings on Privacy Enhancing Technologies· Computer Science
machine prediction:candidate · noneconsensus · none
9
citations
affunlabeled
Privacy-Preserving Federated Recurrent Neural Networks
Sinem Sav, Abdulrahman Diaa, Apostolos Pyrgelis, Jean-Philippe Bossuat, Jean‐Pierre Hubaux
2023· article· en· Proceedings on Privacy Enhancing Technologies· Computer Science
machine prediction:candidate · noneconsensus · none
7
citations
affunlabeled
Beeswax: a platform for private web apps
Jean‐Sébastien Légaré, Róbert Sumi, William Aiello
2016· article· en· Proceedings on Privacy Enhancing Technologies· Computer Science
machine prediction:candidate · noneconsensus · none
6
citations
fundno affunlabeled
Designing a Location Trace Anonymization Contest
Takao Murakami, Hiromi Arai, Koki Hamada, Takuma Hatano, Makoto Iguchi, Hiroaki Kikuchi +10 more
2023· article· en· Proceedings on Privacy Enhancing Technologies· Computer Science
machine prediction:candidate · noneconsensus · none
5
citations
fundno affunlabeled
MLEFlow: Learning from History to Improve Load Balancing in Tor
Hussein Darir, Hussein Sibai, Chin-Yu Cheng, Nikita Borisov, Geir E. Dullerud, Sayan Mitra
2021· article· en· Proceedings on Privacy Enhancing Technologies· Computer Science
machine prediction:candidate · noneconsensus · none
5
citations
affunlabeled
Mind the Gap: Ceremonies for Applied Secret Sharing
Bailey Kacsmar, Chelsea Komlo, Florian Kerschbaum, Ian Goldberg
2020· article· en· Proceedings on Privacy Enhancing Technologies· Computer Science
machine prediction:candidate · noneconsensus · none
3
citations

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