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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.

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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.

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 14 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.

affno abstractunlabeled
Intrusion Detection in Contemporary Environments
Tarfa Hamed, Rozita Dara, Stefan C. Kremer
2017· book-chapter· en· Elsevier eBooks· Computer Science
distilled prediction:candidate · metaepi_narrowconsensus · none
1
citations
afffundno abstractunlabeled
Secure and trusted partial grey-box verification
Yixian Cai, George Karakostas, Alan Wassyng
2019· article· en· International Journal of Information Security· Computer Science
distilled prediction:candidate · noneconsensus · none
1
citations
affno abstractunlabeled
Portable Runtime Verification with Smartphones and Optical Codes
Kim Lavoie, Corentin Leplongeon, Simon Varvaressos, Sébastien Gaboury, Sylvain Hallé
2014· book-chapter· en· Lecture notes in computer science· Computer Science
distilled prediction:candidate · metaepi_narrowconsensus · none
1
citations
affno abstractunlabeled
Securing Business Data on Android Smartphones
Mohamed El-Serngawy, Chamseddine Talhi
2014· book-chapter· en· Lecture notes in computer science· Computer Science
distilled prediction:candidate · metaepi_narrow+open_scienceconsensus · none
1
citations
afffundunlabeled
Scaling Multi-Objective Optimization for Clustering Malware
Noah MacAskill, Zachary Wilkins, A. Nur Zincir‐Heywood
2021· article· en· 2021 IEEE Symposium Series on Computational Intelligence (SSCI)· Computer Science
distilled prediction:candidate · metaepi_narrowconsensus · none
1
citations
afffundunlabeled
LockBoost: Detecting Malware Binaries by Locking False Alarms
Anandharaju Durai Raju, Ke Wang
2022· article· en· 2022 International Joint Conference on Neural Networks (IJCNN)· Computer Science
distilled prediction:candidate · metaepi_narrow+insufficient_payloadconsensus · none
1
citations
affno abstractunlabeled
Obfuscation and Optimization
John Aycock
2016· book-chapter· en· Computer Science
distilled prediction:candidate · noneconsensus · none
1
citations
affunlabeled
Minerva: A File-Based Ransomware Detector
Dorjan Hitaj, Giulio Pagnotta, Fabio De Gaspari, Lorenzo De Carli, Luigi V. Mancini
2025· article· en· Computer Science
distilled prediction:candidate · noneconsensus · none
1
citations
affunlabeled
Debugging Video Games: A Systematic Mapping
Adrien Vanègue, Valentin Bourcier, Fábio Petrillo, Steven Costiou
2023· article· en· Computer Science
distilled prediction:candidate · noneconsensus · none
1
citations
affno abstractunlabeled
Machine Learning for Static Malware Analysis
Ziad Mansour, Christopher Molloy, Steven H. H. Ding
2021· book-chapter· en· Computer Science
distilled prediction:candidate · metaepi_narrowconsensus · none
1
citations
affunlabeled
Sample creation not considered harmful
Daniel Medeiros Nunes de Castro, John Aycock
2013· article· en· Computer Science
distilled prediction:candidate · noneconsensus · none
1
citations

How this was built: Screen · Findings · About