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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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Generative Adversarial Networks and Image Synthesis
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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
venuejournal
aboutaboutness

The four routes compose: require the funder route and exclude affiliation to get the funder-only stratum no affiliation-based frame ever sees.

668 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.
668 works in the cohort · of 4,299,418page 14 of 14

Labels cover 1 of 668 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 668 of 668 works in this cohort. Predictions are machine_predicted_unvalidated teacher distillation outputs. Candidate is the union; consensus is the intersection.

affvenueunlabeled
Symmetric Wasserstein Autoencoders
Sun Sun, Hongyu Guo
2021· article· en· NPARC· Computer Science
distilled prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Scoring and Classifying with Gated Auto-Encoders
Daniel Jiwoong Im, Graham W. Taylor
2015· preprint· en· Lecture notes in computer science· Computer Science
distilled prediction:candidate · metaepi_narrow+scholarly_communicationconsensus · none
0
citations
fundno affunlabeled
Training diffusion-based generative models with limited data
Zhaoyu Zhang, Yang; id_orcid 0000-0001-5536-503X Hua, Guanxiong; id_orcid 0000-0003-1901-9097 Sun, Hui; id_orcid 0000-0003-2633-6015 Wang, Sean; id_orcid 0000-0002-3016-6197 McLoone
2025· article· en· Research Portal (Queen's University Belfast)· Computer Science
distilled prediction:candidate · noneconsensus · none
0
citations
affunlabeled
GRIG: Data-Efficient Generative Residual Image Inpainting
Wanglong Lu, Xianta Jiang, Xiaogang Jin, Yongliang Yang, Minglun Gong, Kaijie Shi +2 more
2025· article· en· Computational Visual Media· Computer Science
distilled prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Microphorella vespera, sp. nov.
2022· article· en· Zenodo (CERN European Organization for Nuclear Research)· Computer Science
distilled prediction:candidate · sts+insufficient_payloadconsensus · insufficient_payload
0
citations
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How this was built: Screen · Findings · About