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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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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.

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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.

2,407 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.
2,407 works in the cohort · of 4,299,418page 30 of 49

Labels cover 84 of 2,407 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 2,407 of 2,407 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 guide to conduct a high-quality survey research
Yuki Kotani, Atsushi Kawaguchi, Nobuaki Shime
2021· article· en· Journal of the Japanese Society of Intensive Care Medicine· Decision Sciences
machine prediction:candidate · metaresearchconsensus · none
1
citations
aboutno affunlabeled
Almost everyone in New York is raising PRICEs
Michael Newman, Bill Haddican, Zi Zi Gina Tan
2018· article· en· ScholarlyCommons (University of Pennsylvania)· Decision Sciences
machine prediction:candidate · noneconsensus · none
1
citations
venueaboutno affunlabeled
Observation on the INES Symposium
Robert W. Crocker
2012· article· en· Comparative and International Education· Decision Sciences
machine prediction:candidate · noneconsensus · none
1
citations
affunlabeled
Evaluation of Knowledge to Action
Onil Bhattacharyya, Merrick Zwarenstein, Deborah J. Kenny, Evelyn Cornelissen, Craig Mitton
2009· other· en· Decision Sciences
machine prediction:candidate · noneconsensus · none
1
citations
affunlabeled
Bestiary of Questionable Research Practices in Psychology
Tamás Nagy, Jane Hergert, Mahmoud Medhat Elsherif, Lukas Wallrich, Kathleen Schmidt, Talia Waltzer +13 more
2024· preprint· en· Decision Sciences
machine prediction:candidate · metaresearch+research_integrityconsensus · metaresearch
1
citations
aboutno affunlabeled
The Canadian M&E System
Robert Lahey
2010· article· en· World Bank Publications· Decision Sciences
machine prediction:candidate · metaresearchconsensus · none
1
citations
aboutno affunlabeled
Police and Problem Solving: Beyond SARA
Michael McGarry
2010· article· en· Australasian Policing· Decision Sciences
machine prediction:candidate · noneconsensus · none
1
citations
affno abstractunlabeled
LogicalOutcomes Evaluation Planning Handbook
G.R. Kerr, Sophie Llewelyn
2024· article· en· SSRN Electronic Journal· Decision Sciences
machine prediction:candidate · noneconsensus · none
0
citations
venueno affno abstractunlabeled
10.1016/s1541-9800(07)70399-x
2000· article· en· Time to knit· Decision Sciences
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
aboutno affunlabeled
Beyond implementation
Daniella Bendo, Dustin Ciufo, Christine Goodwin-De Faria
2025· book-chapter· en· Decision Sciences
machine prediction:candidate · noneconsensus · none
0
citations

How this was built: Screen · Findings · About