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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.

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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.

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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 32 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.

afffundunlabeled
Malliavin calculus in a binomial framework
Samuel N. Cohen, Robert J. Elliott, Tak Kuen Siu
2018· article· en· Applied Stochastic Models in Business and Industry· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Optimal Portfolio Allocation with Hedge Funds
René García, Marcel Rindisbacher, Jérôme Detemple
2009· article· en· SSRN Electronic Journal· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
afffundunlabeled
On Krylov’s estimates for optional semimartingales
Mohamed Abdelghani, Alexander Melnikov, Andrey Pak
2021· article· en· Random Operators and Stochastic Equations· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
fundno affno abstractunlabeled
Stratified Monte Carlo simulation of Markov chains
Rana Fakhereddine, Rami El Haddad, Christian Lécot
2016· preprint· en· Mathematics and Computers in Simulation· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
TOPS: Transition-Based Volatility-Reduced Policy Search
Liangliang Xu, Daoming Lyu, Yangchen Pan, Aiwen Jiang, Bo Liu
2022· book-chapter· en· Lecture notes in computer science· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Backward SDEs with superquadratic growth
Freddy Delbaen, Ying Hu, Xiaobo Bao
2009· preprint· en· arXiv (Cornell University)· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
venueno affunlabeled
Estimation of Smooth Functions via Convex Programs
Eunji Lim, Mina Attallah
2016· article· en· International Journal of Statistics and Probability· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Balance Laws
Henning Struchtrup
2024· book-chapter· en· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
venueno affunlabeled
10.51847/untJ4oFIhC
2000· article· en· Time to knit· Economics, Econometrics and Finance
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
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