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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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Stochastic processes and financial applications
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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
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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.

1,930 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.
1,930 works in the cohort · of 4,299,418page 33 of 39

Labels cover 4 of 1,930 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 1,930 of 1,930 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.

venueno affunlabeled
Multitouch Options
Tristan Guillaume
2023· article· en· Journal of risk and financial management· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
A jump process filter
Robert J. Elliott, Lakhdar Aggoun
2002· article· en· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Understanding Equity Option Prices
Mathieu Fournier, Peter Christoffersen, Kris Jacobs
2012· article· en· SSRN Electronic Journal· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
afffundunlabeled
FINANCIAL SIGNAL PROCESSING: A SELF CALIBRATING MODEL
Robert J. Elliott, William C. Hunter, Barbara M. Jamieson
2001· preprint· en· International Journal of Theoretical and Applied Finance· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Random Measures
Samuel N. Cohen, Robert J. Elliott
2015· book-chapter· en· Probability and its applications· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Short-Term Portfolio Risk
Mary R. Hardy, David Saunders
2022· book-chapter· en· Cambridge University Press eBooks· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Pricing the CBOT T-Bonds Futures
Michèle Breton, Hatem Ben‐Ameur, Ramzi Ben Abdallah
2006· article· fr· Les Cahiers du GERAD· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Static Fund Separation of Long Term Investments
Paolo Guasoni, Scott Robertson
2011· article· en· SSRN Electronic Journal· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Concluding Thoughts and Next Steps
Narat Charupat, Huaxiong Huang, Moshe A. Milevsky
2012· book-chapter· en· Cambridge University Press eBooks· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations

How this was built: Screen · Findings · About