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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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Advanced Bandit Algorithms Research
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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
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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.

436 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.
436 works in the cohort · of 4,299,418page 2 of 9

Labels cover 1 of 436 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 436 of 436 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
The Online Loop-free Stochastic Shortest-Path Problem.
Gergely Neu, András György, Csaba Szepesvári
2010· article· en· SZTAKI Publication Repository (Hungarian Academy of Sciences)· Decision Sciences
machine prediction:candidate · noneconsensus · none
32
citations
affunlabeled
Conservative Bandits
Yifan Wu, Roshan Shariff, Tor Lattimore, Csaba Szepesvári
2016· article· en· arXiv (Cornell University)· Decision Sciences
machine prediction:candidate · noneconsensus · none
31
citations
affunlabeled
Online Learning with Global Cost Functions
Eyal Even-Dar, Robert Kleinberg, Shie Mannor, Yishay Mansour
2009· article· en· Decision Sciences
machine prediction:candidate · noneconsensus · none
31
citations
afffundno abstractunlabeled
Reinforcement Learning in Economics and Finance
Arthur Charpentier, Romuald Élie, Carl Remlinger
2021· preprint· en· Computational Economics· Decision Sciences
machine prediction:candidate · noneconsensus · none
30
citations
affunlabeled
Online Learning under Delayed Feedback
Pooria Joulani, András György, Csaba Szepesvári
2013· preprint· en· arXiv (Cornell University)· Decision Sciences
machine prediction:candidate · noneconsensus · none
29
citations
affunlabeled
{Bayesian Multi-Scale Optimistic Optimization}
Ziyu Wang, Babak Shakibi, Jin Lin, Nando de Freitas
2014· article· en· Oxford University Research Archive (ORA) (University of Oxford)· Decision Sciences
machine prediction:candidate · noneconsensus · none
25
citations
affunlabeled
Online learning of quantum states*
2019· article· en· Journal of Statistical Mechanics Theory and Experiment· Decision Sciences
machine prediction:candidate · noneconsensus · none
22
citations
afffundunlabeled
Regret Bounds for Batched Bandits
Hossein Esfandiari, Amin Karbasi, Abbas Mehrabian, Vahab Mirrokni
2021· article· en· Proceedings of the AAAI Conference on Artificial Intelligence· Decision Sciences
machine prediction:candidate · noneconsensus · none
21
citations
afffundunlabeled
The Multi-Armed Bandit With Stochastic Plays
Antoine Lesage‐Landry, Joshua A. Taylor
2017· article· en· IEEE Transactions on Automatic Control· Decision Sciences
machine prediction:candidate · noneconsensus · none
20
citations
afffundunlabeled
Online Compact Convexified Factorization Machine
Xiao Lin, Wenpeng Zhang, Min Zhang, Wenwu Zhu, Jian Pei, Peilin Zhao +1 more
2018· article· en· Decision Sciences
machine prediction:candidate · noneconsensus · none
20
citations
affunlabeled
Deep learning games
Dale Schuurmans, Martin Zinkevich
2016· article· en· Neural Information Processing Systems· Decision Sciences
machine prediction:candidate · noneconsensus · none
20
citations
affunlabeled
Fast and Slow Learning From Reviews
Daron Acemoğlu, Ali Makhdoumi, Azarakhsh Malekian, Asuman Ozdaglar
2017· report· en· National Bureau of Economic Research· Decision Sciences
machine prediction:candidate · noneconsensus · none
19
citations
affno abstractunlabeled
Dynamic Pricing with Fairness Constraints
Maxime C. Cohen, Sentao Miao, Yining Wang
2021· article· en· SSRN Electronic Journal· Decision Sciences
machine prediction:candidate · noneconsensus · none
18
citations
affno abstractunlabeled
Online Learning with Constraints
Shie Mannor, John N. Tsitsiklis
2006· book-chapter· en· Lecture notes in computer science· Decision Sciences
machine prediction:candidate · noneconsensus · none
17
citations

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