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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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Network Security and Intrusion Detection
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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
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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.

1,999 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.
1,999 works in the cohort · of 4,299,418page 14 of 40

Labels cover 2 of 1,999 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 1,999 of 1,999 works in this cohort. Predictions are machine_predicted_unvalidated teacher distillation outputs. Candidate is the union; consensus is the intersection.

affunlabeled
Midas: Microcluster-Based Detector of Anomalies in Edge Streams
Siddharth Bhatia, Bryan Hooi, Minji Yoon, Kijung Shin, Christos Faloutsos
2020· preprint· en· Proceedings of the AAAI Conference on Artificial Intelligence· Computer Science
distilled prediction:candidate · metaepi_narrowconsensus · none
10
citations
aboutno affunlabeled
Overview and Exploratory Analyses of CICIDS 2017 Intrusion Detection Dataset
Akinyemi Moruff OYELAKIN, Ameen A.O, Ogundele T.S, Taofeekat Tosin Salau-Ibrahim, Abdulrauf U.T, Olufadi H.I +3 more
2023· article· en· Journal of Systems Engineering and Information Technology (JOSEIT)· Computer Science
distilled prediction:candidate · noneconsensus · none
10
citations
affno abstractunlabeled
Evolving Buffer Overflow Attacks with Detector Feedback
H. Güneş Kayacık, Malcolm I. Heywood, A. Nur Zincir‐Heywood
2007· book-chapter· en· Lecture notes in computer science· Computer Science
distilled prediction:candidate · metaepi_narrowconsensus · none
10
citations
affunlabeled
WIDS
C. I. Ezeife, Maxwell Ejelike, A. K. Aggarwal
2008· article· en· Computer Science
distilled prediction:candidate · noneconsensus · none
9
citations
affunlabeled
Resilience properties and metrics: how far have we gone?
Thomas Clédel, Nora Cuppens, Frédéric Cuppens, Romain Dagnas
2020· article· en· Journal of Surveillance Security and Safety· Computer Science
distilled prediction:candidate · noneconsensus · none
9
citations
afffundunlabeled
Machine Learning for DoS Attack Detection in IoT Systems
Brunel Rolack Kikissagbe, Mehdi Adda, Paul Célicourt, Amro Najjar
2024· article· en· Procedia Computer Science· Computer Science
distilled prediction:candidate · scholarly_communicationconsensus · none
9
citations
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