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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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Advanced Malware Detection Techniques
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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.

affaffiliation
fundfunder
venuejournal
aboutaboutness

The four routes compose: require the funder route and exclude affiliation to get the funder-only stratum no affiliation-based frame ever sees.

977 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.
977 works in the cohort · of 4,299,418page 7 of 20

Labels cover 1 of 977 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 977 of 977 works in this cohort. Predictions are machine_predicted_unvalidated teacher distillation outputs. Candidate is the union; consensus is the intersection.

affunlabeled
LARGE-SCALE MALWARE EXPERIMENTS: WHY, HOW, AND SO WHAT?
Joan Vivancos Calvet, José M. Fernandez, Pierre-Marc Bureau, Jean-Yves Marion
2010· article· en· PolyPublie (École Polytechnique de Montréal)· Computer Science
distilled prediction:candidate · metaepi_narrow+scholarly_communicationconsensus · none
9
citations
affunlabeled
An Analysis of Android Malware Behavior
Fehmi Jaafar, Gagandeep Singh, Pavol Zavarsky
2018· article· en· Computer Science
distilled prediction:candidate · noneconsensus · none
8
citations
affunlabeled
Tamper resistant software
J. R. Nickerson, Stanley Chow, Harold J. Johnson
2001· article· en· Computer Science
distilled prediction:candidate · noneconsensus · none
8
citations
affunlabeled
HearMeOut
Joongyum Kim, Ji‐Hwan Kim, Seongil Wi, Yongdae Kim, Sooel Son
2022· article· en· Computer Science
distilled prediction:candidate · noneconsensus · none
8
citations
affunlabeled
Human Factors in Cybersecurity
Xichen Zhang, Ali A. Ghorbani
2019· book-chapter· en· Advances in information security, privacy, and ethics book series· Computer Science
distilled prediction:candidate · metaepi_narrow+scholarly_communication+research_integrityconsensus · none
8
citations
venueno affunlabeled
Cyber Security amid COVID-19
Hussin Hejase, Hasan Fayyad-Kazan, Ale J. Hejase, Imad Moukadem
2021· article· en· Computer and Information Science· Computer Science
distilled prediction:candidate · noneconsensus · none
8
citations
affno abstractunlabeled
Adversarial Example Games
Joey Bose, Gauthier Gidel, Hugo Berard, Andre Cianflone, Pascal Vincent, Simon Lacoste-Julien +1 more
2020· article· en· Neural Information Processing Systems· Computer Science
distilled prediction:candidate · noneconsensus · none
8
citations
affno abstractunlabeled
GenAI Application Level Security
Ken Huang, Grace Huang, Adam Dawson, Daniel Wu
2024· book-chapter· en· Future of business and finance· Computer Science
distilled prediction:candidate · noneconsensus · none
8
citations
affno abstractunlabeled
A survey on run-time packers and mitigation techniques
Ehab M. Alkhateeb, Ali A. Ghorbani, Arash Habibi Lashkari
2023· article· en· International Journal of Information Security· Computer Science
distilled prediction:candidate · noneconsensus · none
8
citations
affno abstractunlabeled
A New Approach to Malware Detection
Hongying Tang, Bo Zhu, Kui Ren
2009· book-chapter· en· Lecture notes in computer science· Computer Science
distilled prediction:candidate · metaepi_narrowconsensus · none
7
citations

How this was built: Screen · Findings · About