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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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Digital and Cyber Forensics
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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.

257 results · 1 filter active ·
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20002025
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Machine labels · sparse coverage
Evidence
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An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
257 works in the cohort · of 4,299,418page 2 of 6

Labels cover 1 of 257 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 257 of 257 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
Sniper forensics
Lynn Greiner
2009· article· en· netWorker· Computer Science
machine prediction:candidate · noneconsensus · none
7
citations
affunlabeled
Content-based File Type Identification
Kireet Bhat, Jason Lam, Farhana Zulkernine
2018· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
6
citations
venueno affno abstractunlabeled
Electronic Records as Documentry Evidence
Ken Chasse
2007· article· en· Canadian journal of law and technology· Computer Science
machine prediction:candidate · noneconsensus · none
5
citations
fundno affno abstractunlabeled
A Consistency Study of the Windows Registry
Yuandong Zhu, Joshua I. James, Pavel Gladyshev
2010· book-chapter· en· IFIP International Federation for Information Processing/IFIP· Computer Science
machine prediction:candidate · noneconsensus · none
5
citations
affno abstractunlabeled
Forensic Analysis of the iOS Apple Pay Mobile Payment System
Trevor T. Nicholson, Darren Hayes, Nhien‐An Le‐Khac
2023· book-chapter· en· IFIP advances in information and communication technology· Computer Science
machine prediction:candidate · noneconsensus · none
3
citations
aboutno affunlabeled
InterPARES: Securing the Future of Our Electronic Records
Ciaran B. Trace, Shelby Sanett
2000· article· en· Bulletin of the American Society for Information Science and Technology· Computer Science
machine prediction:candidate · scholarly_communicationconsensus · none
3
citations
aboutno affunlabeled
Privacy by Design and Language Resources.
Paweł Kamocki, Andreas Witt
2020· article· en· Publication Server of the Institute for German Language (Institute for German Language)· Computer Science
machine prediction:candidate · noneconsensus · none
3
citations
affno abstractunlabeled
File Signature Searching Forensics
Xiaodong Lin
2018· book-chapter· en· Computer Science
machine prediction:candidate · noneconsensus · none
3
citations
affunlabeled
Special issue on social network security and privacy
Mirosław Kutyłowski, Yu Wang, Shouhuai Xu, Laurence T. Yang
2018· article· en· Concurrency and Computation Practice and Experience· Computer Science
machine prediction:candidate · noneconsensus · none
2
citations
affno abstractunlabeled
Offender Profiling and Crime Analysis
Jennifer L. Schulenberg, Peter J. Carrington
2004· article· en· International Criminal Justice Review· Computer Science
machine prediction:candidate · noneconsensus · none
2
citations
affno abstractunlabeled
Distributed Filesystem Forensics: Ceph as a Case Study
Krzysztof Nagrabski, Michael J. Hopkins, Milda Petraityte, Ali Dehghantanha, Reza M. Parizi, Gregory Epiphaniou +1 more
2019· book-chapter· en· Computer Science
machine prediction:candidate · noneconsensus · none
2
citations
venueno affunlabeled
Micro Cloud Services Forensics as a Framework
Abubakr Shehata, Heba K. Aslan, Young Im Cho, Mohamed S. Abdallah
2024· article· en· International Journal of Safety and Security Engineering· Computer Science
machine prediction:candidate · noneconsensus · none
2
citations
aboutno affunlabeled
DETEKSI SERANGAN DDoS MENGGUNAKAN Q-LEARNING
Wulan Sri Lestari
2022· article· id· JATISI (Jurnal Teknik Informatika dan Sistem Informasi)· Computer Science
machine prediction:candidate · noneconsensus · none
2
citations
affunlabeled
High Performance Proactive Digital Forensics
Soltan Alharbi, Belaid Moa, Jens H. Weber-Jahnke, Issa Traoré
2012· article· en· Journal of Physics Conference Series· Computer Science
machine prediction:candidate · noneconsensus · none
2
citations
fundno affno abstractunlabeled
Digital Forensics and Cyber Crime
2024· book· en· Lecture notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering· Computer Science
machine prediction:candidate · noneconsensus · none
2
citations

How this was built: Screen · Findings · About