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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 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.

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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 4 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.

afffundunlabeled
Graph-Based Compression for Distributed Particle Filters
Jun Ye Yu, Mark Coates, Michael Rabbat
2019· article· en· IEEE Transactions on Signal and Information Processing over Networks· Computer Science
machine prediction:candidate · noneconsensus · none
9
citations
afffundunlabeled
Building a Disease Knowledge Graph
Enayat Rajabi, Somayeh Kafaie
2023· article· en· Studies in health technology and informatics· Computer Science
machine prediction:candidate · noneconsensus · none
7
citations
affunlabeled
Node-Centric Pruning: A Novel Graph Reduction Approach
Hossein Shokouhinejad, Roozbeh Razavi‐Far, Griffin Higgins, Ali A. Ghorbani
2024· article· en· Machine Learning and Knowledge Extraction· Computer Science
machine prediction:candidate · noneconsensus · none
6
citations
afffundunlabeled
Learnable Filters for Geometric Scattering Modules
Alexander Tong, Frederik Wenkel, Dhananjay Bhaskar, Kincaid Macdonald, Jackson Grady, Michael Perlmutter +2 more
2024· article· en· IEEE Transactions on Signal Processing· Computer Science
machine prediction:candidate · noneconsensus · none
6
citations
affunlabeled
Graph Contrastive Learning for Truth Inference
Hao Liu, Jiacheng Liu, Feilong Tang, Peng Li, Long Chen, Jiadi Yu +4 more
2024· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
6
citations
affunlabeled
dynnode2vec: Scalable Dynamic Network Embedding
Sedigheh Mahdavi, Shima Khoshraftar, Aijun An
2018· preprint· en· arXiv (Cornell University)· Computer Science
machine prediction:candidate · noneconsensus · none
5
citations

How this was built: Screen · Findings · About