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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.

37,702 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.
37,702 works in the cohort · of 4,299,418page 224 of 755

Labels cover 42 of 37,702 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 37,702 of 37,702 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
Hans Kelsen on Norm and Language
William E. Conklin
2006· article· en· SSRN Electronic Journal· Arts and Humanities
machine prediction:candidate · noneconsensus · none
2
citations
affno abstractunlabeled
Do Private Equity Firms Pay for Synergies?
Benjamin Hammer, Denis Schweizer, Bernhard Schwetzler
2018· article· en· SSRN Electronic Journal· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
2
citations
affno abstractunlabeled
Automatability and Capital Structure
Jiaping Qiu, Chi Wan, Yan Wang
2020· article· en· SSRN Electronic Journal· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
2
citations
affno abstractunlabeled
The Carbon Abatement Game
Christoph Hambel, Holger Kraft, Eduardo S. Schwartz
2018· article· en· SSRN Electronic Journal· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
2
citations
affaboutno abstractunlabeled
How Monetary Policy is Made: Two Canadian Tales
Pierre L. Siklos, Matthias Neuenkirch
2013· article· en· SSRN Electronic Journal· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
2
citations
affno abstractunlabeled
Navigating the Dimensions of Policy Agendas
Christian Breunig, Samuel Workman
2010· article· en· SSRN Electronic Journal· Social Sciences
machine prediction:candidate · noneconsensus · none
2
citations
affno abstractunlabeled
Stochastic Sequential Screening
Hao Li, Xianwen Shi
2024· preprint· en· SSRN Electronic Journal· Decision Sciences
machine prediction:candidate · noneconsensus · none
2
citations
affno abstractunlabeled
What Information Drives Asset Prices?
Anisha Ghosh, George M. Constantinides
2017· article· en· SSRN Electronic Journal· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
2
citations
affno abstractunlabeled
EU and NATO Enlargement Puzzles
Ivan Katchanovski
2010· article· en· SSRN Electronic Journal· Social Sciences
machine prediction:candidate · noneconsensus · none
2
citations

How this was built: Screen · Findings · About