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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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Crime, Illicit Activities, and Governance
Retraction
Abstract
Evidence source
Study design
Label agreement
Label status

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.

940 results · 1 filter active ·
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20002025
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Machine labels · sparse coverage
Evidence
Language
Type
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An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
940 works in the cohort · of 4,299,418page 15 of 19

Labels cover 1 of 940 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 940 of 940 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
Information and policing
Shota Ichihashi
2025· article· en· Journal of Economic Theory· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
"Anti-Money Laundering in Russia"
Marina Aksenova, Tatiana S. Minaeva
2008· article· en· Research at the University of Copenhagen (University of Copenhagen)· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
A criminologia cultural continuada
Keith John Hayward, Jeff Ferrell
2018· book-chapter· pt· Research at the University of Copenhagen (University of Copenhagen)· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Pleasurable substances and regulation: old wine in new rules?
T. Decorte, D. Zaitch, Sub Criminologie, RENFORCE / Regulering en handhaving
2016· article· nl· Utrecht University Repository (Utrecht University)· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
venueaboutno affunlabeled
Don’t Ever Think You’ve Cracked It!
Ian J. Hopkins
2022· article· en· The Journal of Intelligence Conflict and Warfare· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Book Review: Armed Robbery
Petra Jonas
2003· article· en· International Criminal Justice Review· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
CONTRABANDO E PIRATARIA
Paulo Henrique Marcusso Kawashita
2023· article· pt· Revista (RE)DEFINIÇÕES DAS FRONTEIRAS· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
venueno affunlabeled
Playing for a Just World
Rahul Varma
2004· article· en· Canadian Theatre Review· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Thinking about the prevention of organised crime
David C. Hicks
2007· dissertation· en· ORCA Online Research @Cardiff (Cardiff University)· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
venueno affunlabeled
Violencia, necropolítica y capitalocene en Cromo
María del Carmen Caña Jiménez
2018· article· es· Revista Canadiense de Estudios Hispánicos· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations

How this was built: Screen · Findings · About