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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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Gambling Behavior and Treatments
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Abstract
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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
aboutaboutness

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

2,819 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.
2,819 works in the cohort · of 4,299,418page 52 of 57

Labels cover 14 of 2,819 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 2,819 of 2,819 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.

affno abstractunlabeled
Correction to: Self-Generated Motives of Social Casino Gamers
Hyoun S. Kim, Sophia Coelho, Michael J. A. Wohl, Matthew Rockloff, Daniel S. McGrath, David C. Hodgins
2022· erratum· en· Journal of Gambling Studies· Psychology
machine prediction:candidate · noneconsensus · none
0
citations
affvenueno abstractunlabeled
Gambling: Who Wins? Who Loses?
Nigel E. Turner
2006· article· en· Journal of Gambling Issues· Psychology
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Older Adult Gamblers
M. Fontaine, Céline Lemercier, Céline Bonnaire, Isabelle Giroux, Jacques Py, Isabelle Varescon +1 more
2023· preprint· en· HAL (Le Centre pour la Communication Scientifique Directe)· Psychology
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Analysis of AI in Roulette - Machines Becoming Humans
Niev Sanghvi, Rahul Shankar Pachpande, Durgesh Hiralal Pawar, Tanishq Gandhi, Tejjas Bhingardevay, Paarth Pandey
2025· article· Zenodo (CERN European Organization for Nuclear Research)· Psychology
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Analysis of AI in Roulette - Machines Becoming Humans
Niev Sanghvi, Rahul Shankar Pachpande, Durgesh Hiralal Pawar, Tanishq Gandhi, Tejjas Bhingardevay, Paarth Pandey
2025· article· Zenodo (CERN European Organization for Nuclear Research)· Psychology
machine prediction:candidate · noneconsensus · none
0
citations
venueaboutno affunlabeled
The Issue of Legalized Gambling in Canada
Ayesha Kapadia
2012· article· en· HPS The Journal of History and Political Science· Psychology
machine prediction:candidate · noneconsensus · none
0
citations
venueno affno abstractunlabeled
10.1016/s9999-9994(09)20590-3
2000· article· en· Time to knit· Psychology
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations

How this was built: Screen · Findings · About