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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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Canadian Policy and Governance
Retraction
Abstract
Evidence source
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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.

9,787 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.
9,787 works in the cohort · of 4,299,418page 85 of 196

Labels cover 3 of 9,787 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 9,787 of 9,787 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.

aboutno affunlabeled
Preface
Evan H. Potter
2008· book-chapter· en· McGill-Queen's University Press eBooks· Social Sciences
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
aboutno affno abstractunlabeled
Canada invests in the future
Cordelia Sealy
2004· article· en· Materials Today· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affno abstractunlabeled
13 Will Canada “Be There”?
Timothy Andrews Sayle
2025· book-chapter· University of British Columbia Press eBooks· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
venueaboutno affunlabeled
Getting to a Better Canadian Healthcare System
William E. Gardner, Katherine Fierlbeck, Adrian R. Levy
2014· article· en· A Nudge Too Far? A Nudge at All? On Paying People to Be Healthy· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Trump hails NAFTA revamp
2018· other· en· Internet Archive (Internet Archive)· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
venueaboutno affunlabeled
Issue Information
2016· paratext· fr· Canadian Journal of Economics/Revue canadienne d économique· Social Sciences
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
afffundaboutunlabeled
Frontmatter
Greg Anderson, Geoffrey Hale
2021· book-chapter· en· University of Toronto Press eBooks· Social Sciences
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
aboutno affno abstractunlabeled
Perverse subsidy reform in Canada
Nicola Anthony Contini
2003· dissertation· en· PRISM (University of Calgary)· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affaboutunlabeled
Frontmatter
Pablo Heidrich, Laura Macdonald
2022· book-chapter· en· University of Toronto Press eBooks· Social Sciences
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
affaboutno abstractunlabeled
Canada: Political developments and data in 2020
David Stewart
2021· article· en· European Journal of Political Research Political Data Yearbook· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affno abstractunlabeled
Basic statistics of Canada, 2012
2014· book-chapter· en· OECD economic surveys. Canada· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Taking Monetary Aggregates Seriously
Pierre L. Siklos
2010· article· en· e-briefs· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affaboutno abstractunlabeled
Canada: Political Developments and Data in 2019
David Stewart
2020· article· en· European Journal of Political Research Political Data Yearbook· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affaboutunlabeled
Frontmatter
Heather Whiteside
2020· book-chapter· en· University of Toronto Press eBooks· Social Sciences
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
venueno affunlabeled
Interview with Peter Kresl
Peter Karl Kresl, Entrevue Avec, Peter Kresl Entrevue
2008· article· fr· Interventions économiques· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affaboutno abstractunlabeled
Canada: Political development and data for 2017
David Stewart
2018· article· en· European Journal of Political Research Political Data Yearbook· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Frontmatter
2012· book-chapter· en· University of Toronto Press eBooks· Social Sciences
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
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