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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 11 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
Programmatic Strategies for Real-Time Strategy Games
Julian R. H. Mariño, Rubens O. Moraes, Tassiana C. Oliveira, Cláudio Fabiano Motta Toledo, Levi H. S. Lelis
2021· article· en· Proceedings of the AAAI Conference on Artificial Intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
8
citations
afffundunlabeled
Towards Cohesive Anomaly Mining
Yun Xiong, Yangyong Zhu, Philip S. Yu, Jian Pei
2013· article· en· Proceedings of the AAAI Conference on Artificial Intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
7
citations
affunlabeled
Test-Time Personalization with Meta Prompt for Gaze Estimation
Huan Liu, Julia Qi, Zhenhao Li, Mohammad Hassanpour, Yang Wang, Konstantinos N. Plataniotis +1 more
2024· article· en· Proceedings of the AAAI Conference on Artificial Intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
7
citations
afffundunlabeled
Optimal Sparse Regression Trees
Rui Zhang, Rui Xin, Margo Seltzer, Cynthia Rudin
2023· article· en· Proceedings of the AAAI Conference on Artificial Intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
7
citations
affunlabeled
The Metric Distortion of Multiwinner Voting
Ioannis Caragiannis, Nisarg Shah, Alexandros A. Voudouris
2022· article· en· Proceedings of the AAAI Conference on Artificial Intelligence· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
7
citations
affunlabeled
XClusters: Explainability-First Clustering
Hyunseung Hwang, Steven Euijong Whang
2023· article· en· Proceedings of the AAAI Conference on Artificial Intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
7
citations
afffundunlabeled
Detecting Semantic Anomalies
Faruk Ahmed, Aaron Courville
2020· preprint· en· Proceedings of the AAAI Conference on Artificial Intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
7
citations
affunlabeled
Deep Probabilistic Canonical Correlation Analysis
Mahdi Karami, Dale Schuurmans
2021· article· en· Proceedings of the AAAI Conference on Artificial Intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
6
citations

How this was built: Screen · Findings · About