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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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Cybercrime and Law Enforcement Studies
Retraction
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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.

473 results · 1 filter active ·
Results by year
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.
473 works in the cohort · of 4,299,418page 8 of 10

Labels cover 1 of 473 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 473 of 473 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
Toward a Cyberlegal Culture.
Marylin Johnson Raisch
2002· article· en· International Journal of Legal Information· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Een gezamenlijke rekening?
Bram Klievink, Rolf van Wegberg, Michel van Eeten
2017· article· en· Bestuurskunde· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
venueno affunlabeled
The Legal Framework of Electronic Data Crimes
Shayma Muhammed Saeed, Ali Ahmad Al Zubi
2014· article· en· Canadian social science· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Unmasking the Threat
M Beemamol
2024· book-chapter· en· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
List of Authors
2023· other· en· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
venueno affno abstractunlabeled
Big Deal Identity Theft
Martin Nemzow
2003· article· en· The Journal of Internet Banking and Commerce· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Crime Online
Reda Alhajj, Jon Rokne
2014· book-chapter· en· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affno abstractunlabeled
Crime in Online Communities
Reda Alhajj, Jon Rokne
2018· book-chapter· en· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
venueaboutno affunlabeled
Data Analytics and Security Policy
CASIS
2020· article· en· The Journal of Intelligence Conflict and Warfare· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Malware and trojans and intrusions...oh my
Saurabh Bagchi, John Viega, Ben A. Calloni, Kathy Wang
2008· article· en· Annual Information Security Symposium· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Crime Online
Reda Alhajj, Jon Rokne
2018· book-chapter· en· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
venueno affunlabeled
A Small Town Texas Fraud
Gordon Heslop
2018· article· en· Journal of Applied Business and Economics· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations

How this was built: Screen · Findings · About