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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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Proceedings of the AAAI Conference on Artificial Intelligence
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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.

1,046 results · 1 filter active ·
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20102025
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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.
1,046 works in the cohort · of 4,299,418page 13 of 21

Labels cover 0 of 1,046 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 1,046 of 1,046 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
Fast and Accurate Predictions of IDA*'s Performance
Levi H. S. Lelis, Sandra Zilles, Robert C. Holte
2021· article· en· Proceedings of the AAAI Conference on Artificial Intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
5
citations
affunlabeled
Cost-Sensitive Learning to Rank
Ryan McBride, Ke Wang, Zhouyang Ren, Wenyuan Li
2019· article· en· Proceedings of the AAAI Conference on Artificial Intelligence· Decision Sciences
machine prediction:candidate · noneconsensus · none
5
citations
affunlabeled
Infusing Human Factors into Algorithmic Crowdsourcing
Han Yu, Chunyan Miao, Zhiqi Shen, Jun Lin, Cyril Leung, Qiang Yang
2016· article· en· Proceedings of the AAAI Conference on Artificial Intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
5
citations
afffundunlabeled
Pay to (Not) Play: Monetizing Impatience in Mobile Games
Taylor Lundy, Narun Raman, Hu Fu, Kevin Leyton‐Brown
2024· article· en· Proceedings of the AAAI Conference on Artificial Intelligence· Social Sciences
machine prediction:candidate · noneconsensus · none
5
citations
afffundunlabeled
Sparsification of Decomposable Submodular Functions
Akbar Rafiey, Yuichi Yoshida
2022· article· en· Proceedings of the AAAI Conference on Artificial Intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
5
citations
affunlabeled
Partitioning Friends Fairly
Lily Li, Evi Micha, Aleksandar Nikolov, Nisarg Shah
2023· article· en· Proceedings of the AAAI Conference on Artificial Intelligence· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
5
citations
affunlabeled
Learning Options with Interest Functions
Khimya Khetarpal, Doina Precup
2019· article· en· Proceedings of the AAAI Conference on Artificial Intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
5
citations
affunlabeled
Region-Based Global Reasoning Networks
Chuanming Wang, Huiyuan Fu, Charles X. Ling, Peilun Du, Huadóng Ma
2020· article· en· Proceedings of the AAAI Conference on Artificial Intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
4
citations
fundno affunlabeled
Scaling Trends for Data Poisoning in LLMs
Dillon Bowen, Brendan Murphy, Will Cai, David Khachaturov, Adam Gleave, Kellin Pelrine
2025· article· en· Proceedings of the AAAI Conference on Artificial Intelligence· Decision Sciences
machine prediction:candidate · noneconsensus · none
4
citations
afffundunlabeled
Progression of Decomposed Situation Calculus Theories
Denis Ponomaryov, Mikhail Soutchanski
2013· article· en· Proceedings of the AAAI Conference on Artificial Intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
4
citations
affunlabeled
Adversarial Dropout for Recurrent Neural Networks
Sungrae Park, Kyungwoo Song, Mingi Ji, Wonsung Lee, Il‐Chul Moon
2019· article· en· Proceedings of the AAAI Conference on Artificial Intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
4
citations
affunlabeled
Are Expressive Models Truly Necessary for Offline RL?
Guan Wang, Jianxiong Li, Li Jiang, Juwei Hu, Xianyuan Zhan
2025· article· en· Proceedings of the AAAI Conference on Artificial Intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
4
citations
affunlabeled
Generalized Adversarially Learned Inference
Yatin Dandi, Homanga Bharadhwaj, Abhishek Kumar, Piyush Rai
2021· article· en· Proceedings of the AAAI Conference on Artificial Intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
4
citations

How this was built: Screen · Findings · About