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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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Misinformation and Its Impacts
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
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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.

1,959 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.
1,959 works in the cohort · of 4,299,418page 39 of 40

Labels cover 16 of 1,959 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 1,959 of 1,959 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
WATCH Miss Earth 2022 Live Grand Finale Online Free
2022· article· en· Zenodo (CERN European Organization for Nuclear Research)· Social Sciences
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
affunlabeled
Virginia Journal of Public Health
Natalie E. Cook, Sophie Wenzel, Rachel Silverman, Danielle Short, Kristina Ashleigh Jiles, Teresa Markwalter +1 more
2022· article· en· VTechWorks (Virginia Tech)· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
El Calendario Muisca
2009· other· es· Bulletin of Miscellaneous Information (Royal Gardens Kew)· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
venueno affno abstractunlabeled
Dossier To Combat Disinformation Introduction
Esteban Zunino, Ana Regina Rêgo
2024· article· en· The International Review of Information Ethics· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
THE CRIME OF THE CANADIAN BANKING SYSTEM
2007· other· en· Bulletin of Miscellaneous Information (Royal Gardens Kew)· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Fake News During the COVID-19
Haoqi Geng, Sirui Luo, Hongyezi Zuo
2022· book-chapter· en· Advances in Social Science, Education and Humanities Research/Advances in social science, education and humanities research· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
News, Politics, and Negativity
Stuart Soroka, Stephen McAdams
2012· preprint· en· eScholarship@McGill (McGill)· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Misinformation Resilience
Shelley Boulianne
2022· dataset· en· Figshare· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Can Fact-checkers Discipline the Government?
Samuel Solgon Santos, Marcelo de Carvalho Griebeler
2024· article· en· SSRN Electronic Journal· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Transparency Trends around the World
2017· article· en· eYLS (Yale Law School)· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations

How this was built: Screen · Findings · About