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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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Image and Video Quality Assessment
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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.

589 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.
589 works in the cohort · of 4,299,418page 11 of 12

Labels cover 0 of 589 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 589 of 589 works in this cohort. Predictions are machine_predicted_unvalidated teacher distillation outputs. Candidate is the union; consensus is the intersection.

affunlabeled
LiV: Live DASH Streaming for Volumetric Video
Amir Allahveran, Reza Hedayati Majdabadi, Mea Wang
2025· article· Computer Science
distilled prediction:candidate · metaepi_narrow+scholarly_communicationconsensus · none
0
citations
affno abstractunlabeled
Crowdsourcing Framework for QoE-Aware SD-WAN
Ibtihal Ellawindy, Shahram Shah Heydari
2020· preprint· en· Research Square· Computer Science
distilled prediction:candidate · metaepi_narrow+scholarly_communication+research_integrityconsensus · none
0
citations
affunlabeled
Helping users determine video quality of service settings
Ronald L. Boring, Robert West, Steven C. Moore
2002· article· en· CHI '02 extended abstracts on Human factors in computer systems - CHI '02· Computer Science
distilled prediction:candidate · metaepi_narrowconsensus · none
0
citations
affunlabeled
3D Video Quality Metric for Mobile Applications
Amin Banitalebi-Dehkordi, Mahsa T. Pourazad, Panos Nasiopoulos
2018· preprint· en· arXiv (Cornell University)· Computer Science
distilled prediction:candidate · metaepi_narrowconsensus · none
0
citations
affno abstractunlabeled
Fundamental Concepts in Video
Ze-Nian Li, Mark S. Drew, Jiangchuan Liu
2021· book-chapter· en· Texts in computer science· Computer Science
distilled prediction:candidate · metaepi_narrowconsensus · none
0
citations
affunlabeled
An artifacts-based video quality metric using fuzzy logic
Wei Dai, Zhen Cai, William E. Lynch
2005· article· en· Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE· Computer Science
distilled prediction:candidate · metaepi_narrowconsensus · none
0
citations
affunlabeled
3D Video Quality Metric for 3D Video Compression
Amin Banitalebi-Dehkordi, Mahsa T. Pourazad, Panos Nasiopoulos
2018· preprint· en· arXiv (Cornell University)· Computer Science
distilled prediction:candidate · metaepi_narrowconsensus · none
0
citations
affunlabeled
Image quality of up-converted 2D video from frame-compatible 3D video
Filippo Speranza, Wa James Tam, Carlos Vázquez, Ronald Renaud, Phil Blanchfield
2011· article· en· Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE· Computer Science
distilled prediction:candidate · metaepi_narrowconsensus · none
0
citations

How this was built: Screen · Findings · About