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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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Technology Adoption and User Behaviour
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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
aboutaboutness

The four routes compose: require the funder route and exclude affiliation to get the funder-only stratum no affiliation-based frame ever sees.

1,648 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.
1,648 works in the cohort · of 4,299,418page 4 of 33

Labels cover 4 of 1,648 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 1,648 of 1,648 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
A model of consumer financial numeracy
Bruce A. Huhmann, Shaun McQuitty
2009· article· en· International Journal of Bank Marketing· Decision Sciences
machine prediction:candidate · noneconsensus · none
85
citations
venueno affunlabeled
How Viable Is the UTAUT Model in a Non-Western Context?
Kholoud AlQeisi, Charles Dennis, Ahmed Zakaria Hegazy, Muneer Abbad
2015· article· en· International Business Research· Decision Sciences
machine prediction:candidate · noneconsensus · none
83
citations
affunlabeled
Patterns of B2B e‐commerce usage in SMEs
Ismail Sila, Dawn Dobni
2012· article· en· Industrial Management & Data Systems· Decision Sciences
machine prediction:candidate · noneconsensus · none
71
citations
affunlabeled
Signals of Trustworthiness in E-Commerce
Kathryn M. Kimery, Mary McCord
2006· article· en· Journal of Electronic Commerce in Organizations· Decision Sciences
machine prediction:candidate · noneconsensus · none
69
citations
affaboutunlabeled
Information Systems Effectiveness in Small Businesses
Ana Ortíz de Guinea, Helen Kelley, M. Gordon Hunter
2005· article· en· Journal of Global Information Management· Decision Sciences
machine prediction:candidate · noneconsensus · none
68
citations

How this was built: Screen · Findings · About