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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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Risk and Portfolio Optimization
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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
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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.

710 results · 1 filter active ·
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20002025
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Machine labels · sparse coverage
Evidence
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An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
710 works in the cohort · of 4,299,418page 2 of 15

Labels cover 2 of 710 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 710 of 710 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
A survey of nonlinear robust optimization
Sven Leyffer, Matt Menickelly, Todd Munson, Charlie Vanaret, Stefan M. Wild
2020· article· en· INFOR Information Systems and Operational Research· Decision Sciences
machine prediction:candidate · noneconsensus · none
46
citations
affunlabeled
Star-Shaped Risk Measures
Erio Castagnoli, Giacomo Cattelan, Fabio Maccheroni, Claudio Tebaldi, Ruodu Wang
2022· article· en· Operations Research· Decision Sciences
machine prediction:candidate · noneconsensus · none
45
citations
affno abstractunlabeled
Portfolio Selection and Transactions Costs
Michael J. Best, Jaroslava Hlouskova
2003· article· en· Computational Optimization and Applications· Decision Sciences
machine prediction:candidate · noneconsensus · none
44
citations
affunlabeled
INDIFFERENCE PRICE WITH GENERAL SEMIMARTINGALES
Sara Biagini, Marco Frittelli, Matheus R. Grasselli
2010· article· en· Mathematical Finance· Decision Sciences
machine prediction:candidate · noneconsensus · none
43
citations
affno abstractunlabeled
ChatGPT-Based Investment Portfolio Selection
Oleksandr Romanko, Akhilesh Narayan, Roy H. Kwon
2023· article· en· Operations Research Forum· Decision Sciences
machine prediction:candidate · noneconsensus · none
34
citations
affno abstractunlabeled
Portfolio credit-risk optimization
Ian Iscoe, Alexander Kreinin, Helmut Mausser, Oleksandr Romanko
2012· article· en· Journal of Banking & Finance· Decision Sciences
machine prediction:candidate · noneconsensus · none
33
citations
affunlabeled
How Superadditive Can a Risk Measure Be?
Ruodu Wang, Valeria Bignozzi, Andreas Tsanakas
2015· article· en· SIAM Journal on Financial Mathematics· Decision Sciences
machine prediction:candidate · noneconsensus · none
33
citations
fundno affno abstractunlabeled
CAPM and APT-like models with risk measures
Alejandro Balbás, Beatriz Balbás, Raquel Balbás
2009· article· en· Journal of Banking & Finance· Decision Sciences
machine prediction:candidate · noneconsensus · none
30
citations
affvenueunlabeled
Risk Measures and Portfolio Optimization
Priscilla S.N Gambrah, Traian A. Pirvu
2014· article· en· Journal of risk and financial management· Decision Sciences
machine prediction:candidate · noneconsensus · none
29
citations
afffundno abstractunlabeled
On the mixing set with a knapsack constraint
Ahmad Abdi, Ricardo Fukasawa
2016· article· en· Mathematical Programming· Decision Sciences
machine prediction:candidate · noneconsensus · none
27
citations

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