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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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Digital Marketing and Social Media
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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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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.

1,878 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.
1,878 works in the cohort · of 4,299,418page 23 of 38

Labels cover 2 of 1,878 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 1,878 of 1,878 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.

venueno affunlabeled
Branding in Sustainability
Genni Perlangeli, Andréa Réa
2022· article· en· International Journal of Marketing Studies· Social Sciences
machine prediction:candidate · noneconsensus · none
2
citations
aboutno affunlabeled
A tool for managing brand assets
Chris Bedford
2003· article· en· Design Management Journal (Former Series)· Social Sciences
machine prediction:candidate · noneconsensus · none
2
citations
affunlabeled
E-Marketplaces
Kayvan Miri Lavassani, Bahar Movahedi, Vinod Kumar
2011· book-chapter· en· Advances in e-business research series· Social Sciences
machine prediction:candidate · noneconsensus · none
2
citations
venueno affunlabeled
How Influencer Relations Works
Shannon Gallagher
2021· article· en· Journal of Professional Communication· Social Sciences
machine prediction:candidate · noneconsensus · none
2
citations
affno abstractunlabeled
Digital Consumer Behavior
Eugene Y. Chan
2024· book-chapter· en· Social Sciences
machine prediction:candidate · noneconsensus · none
2
citations
affno abstractunlabeled
The voice as a relationship milestone
Bhavesh Vaghela
2014· article· en· Journal of Direct Data and Digital Marketing Practice· Social Sciences
machine prediction:candidate · noneconsensus · none
2
citations
affvenueunlabeled
Users’ Behaviour in Collaborative Tagging Systems
Samuel Kai Wah Chu, Dinesh Rathi, Helen S. Du
2013· article· fr· Proceedings of the Annual Conference of CAIS / Actes du congrès annuel de l ACSI· Social Sciences
machine prediction:candidate · noneconsensus · none
1
citations
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