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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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Advanced Graph Neural Networks
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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
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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.

518 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.
518 works in the cohort · of 4,299,418page 7 of 11

Labels cover 2 of 518 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 518 of 518 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
Augmenting Knowledge Transfer across Graphs
Yuzhen Mao, Jianhui Sun, Dawei Zhou
2022· article· en· 2022 IEEE International Conference on Data Mining (ICDM)· Computer Science
machine prediction:candidate · noneconsensus · none
1
citations
aboutno affunlabeled
Graph Wavelet Convolutional Network with Graph Clustering
Hiroki Inatsuki, Toshiyuki Uto
2022· article· en· 2022 37th International Technical Conference on Circuits/Systems, Computers and Communications (ITC-CSCC)· Computer Science
machine prediction:candidate · noneconsensus · none
1
citations
affunlabeled
Scaling Graph Propagation Kernels for Predictive Learning
Priyesh Vijayan, Yash Chandak, Mitesh M. Khapra, Srinivasan Parthasarathy, Balaraman Ravindran
2022· article· en· Frontiers in Big Data· Computer Science
machine prediction:candidate · noneconsensus · none
1
citations
affunlabeled
Deep Dynamic Mixed Membership Stochastic Blockmodel
Yu Zheng, Marcin Pietrasik, Marek Reformat
2019· article· en· IEEE/WIC/ACM International Conference on Web Intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
1
citations
affunlabeled
Chapter 17. Approximate Answering of Graph Queries
Michael Cochez, Dimitrios Alivanistos, Erik Arakelyan, Max Berrendorf, Daniel Daza, Mikhail Galkin +3 more
2023· book-chapter· en· Frontiers in artificial intelligence and applications· Computer Science
machine prediction:candidate · noneconsensus · none
1
citations
affno abstractunlabeled
Detection and Defense of Topological Adversarial Attacks on Graphs
Yingxue Zhang, Florence Regol, Soumyasundar Pal, Sakif Khan, Liheng Ma, Mark Coates
2021· article· en· International Conference on Artificial Intelligence and Statistics· Computer Science
machine prediction:candidate · noneconsensus · none
1
citations
aboutno affunlabeled
Graph EquiJoin Dataset
2020· article· en· OSF Preprints (OSF Preprints)· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
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