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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
fundfunder
venuejournal
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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 1 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.

affunlabeled
The Psychology of Fake News
Gordon Pennycook, David G. Rand
2021· review· en· Trends in Cognitive Sciences· Social Sciences
machine prediction:candidate · noneconsensus · none
1,200
citations
affunlabeled
Resistance and Persuasion
Eric S. Knowles, Jay A. Linn
2004· book· en· Psychology Press eBooks· Social Sciences
machine prediction:candidate · noneconsensus · none
980
citations
venueno affunlabeled
Misinformation of COVID-19 on the Internet: Infodemiology Study
Yunam Cuan-Baltazar, María José Muñoz‐Pérez, Carolina Robledo-Vega, Maria Fernanda Pérez-Zepeda
2020· article· en· JMIR Public Health and Surveillance· Social Sciences
machine prediction:candidate · noneconsensus · none
637
citations
fundno affunlabeled
Out-group animosity drives engagement on social media
Steve Rathje, Jay Joseph Van Bavel, Sander van der Linden
2021· article· en· Proceedings of the National Academy of Sciences· Social Sciences
machine prediction:candidate · noneconsensus · none
549
citations
venueno affunlabeled
Fake News: A Definition
Axel Gelfert
2018· article· en· Informal Logic· Social Sciences
machine prediction:candidate · noneconsensus · none
456
citations
affno abstractunlabeled
Deepfakes: Trick or treat?
Jan Kietzmann, Linda W. Lee, Ian P. McCarthy, Tim C. Kietzmann
2019· article· en· Business Horizons· Social Sciences
machine prediction:candidate · noneconsensus · none
449
citations
afffundunlabeled
Reliance on emotion promotes belief in fake news
Cameron Martel, Gordon Pennycook, David G. Rand
2020· article· en· Cognitive Research Principles and Implications· Social Sciences
machine prediction:candidate · noneconsensus · none
447
citations
affunlabeled
Misleading Online Content
Yimin Chen, Niall Conroy, Victoria L. Rubin
2015· article· en· Social Sciences
machine prediction:candidate · noneconsensus · none
429
citations
affunlabeled
AI and the transformation of social science research
Igor Grossmann, Matthew Feinberg, Dawn C. Parker, Nicholas A. Christakis, Philip E. Tetlock, William A. Cunningham
2023· article· en· Science· Social Sciences
machine prediction:candidate · metaresearchconsensus · metaresearch
320
citations
afffundunlabeled
Timing matters when correcting fake news
Nadia M. Brashier, Gordon Pennycook, Adam J. Berinsky, David G. Rand
2021· article· en· Proceedings of the National Academy of Sciences· Social Sciences
machine prediction:candidate · noneconsensus · none
205
citations

How this was built: Screen · Findings · About