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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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Consumer Retail Behavior Studies
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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.

949 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.
949 works in the cohort · of 4,299,418page 2 of 19

Labels cover 3 of 949 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 949 of 949 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
Factors affecting credit card use in India
Arpita Khare, Anshuman Khare, Shveta Singh
2012· article· en· Asia Pacific Journal of Marketing and Logistics· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
78
citations
affunlabeled
Wal‐Mart in Europe: prospects for the UK
Stephen J. Arnold, J. D. Fernie
2000· article· en· International Marketing Review· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
74
citations
affunlabeled
Pull factors of the shopping malls: an empirical study
Cristina Calvo-Porral, Jean-Pierre Lévy-Mangín
2018· article· en· International Journal of Retail & Distribution Management· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
74
citations
affunlabeled
Brands and Urban Life
Sonia Bookman
2013· article· en· Space and Culture· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
68
citations
venueno affunlabeled
Personality Traits Hierarchy of Online Shoppers
Tsai Chen
2011· article· en· International Journal of Marketing Studies· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
60
citations
venueno affno abstractunlabeled
Comparing Online and In-Store Grocery Purchases
Laura Y. Zatz, Alyssa J. Moran, Rebecca L. Franckle, Jason P. Block, Tao Hou, Dan Blue +6 more
2021· article· en· Journal of Nutrition Education and Behavior· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
57
citations
affno abstractunlabeled
Planning food services for a campus setting
Kenneth J. Klassen, Elzbieta Trybus, Arundhati Kumar
2005· article· en· International Journal of Hospitality Management· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
57
citations
affno abstractunlabeled
Profiling shopping mall customers during hard times
Cristina Calvo-Porral, Jean-Pierre Lévy-Mangín
2019· article· en· Journal of Retailing and Consumer Services· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
57
citations
affunlabeled
Consuming in one's mind: An exploration
Alain d’Astous, Jonathan Deschênes
2004· article· en· Psychology and Marketing· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
57
citations
affunlabeled
Compras compulsivas: uma revisão e um relato de caso
Hermano Tavares, Daniela Sabbatini S Lobo, Daniel Fuentes, Donald W. Black
2008· review· pt· Brazilian Journal of Psychiatry· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
53
citations
venueno affno abstractunlabeled
Development and Reliability Testing of a Food Store Observation Form
Leah Rimkus, Lisa M. Powell, Shannon N. Zenk, Euna Han, Punam Ohri‐Vachaspati, Oksana Pugach +5 more
2013· article· en· Journal of Nutrition Education and Behavior· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
51
citations
affaboutunlabeled
Downtowns in transition
Tony Hernández, Ken Jones
2005· article· en· International Journal of Retail & Distribution Management· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
44
citations
venueno affunlabeled
E-Commerce: A Short History Follow-up on Possible Trends
Valdeci Ferreira dos Santos, Leandro Ricardo Sabino, Greiciele Macedo Morais, Carlos Alberto Gonçalves
2017· article· en· International Journal of Business Administration· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
42
citations
afffundno abstractunlabeled
Co-creating affective atmospheres in retail experience
Annamma Joy, Jeff Jianfeng Wang, Davide C. Orazi, Seyee Yoon, Kathryn A. LaTour, Camilo Peña
2023· article· en· Journal of Retailing· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
42
citations

How this was built: Screen · Findings · About