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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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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.

1,448 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.
1,448 works in the cohort · of 4,299,418page 9 of 29

Labels cover 4 of 1,448 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 1,448 of 1,448 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.

affno abstractunlabeled
The Use of Diagrams in Science
Lillian P. Fanjoy, A. Luke MacNeill, Lisa A. Best
2012· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
14
citations
affunlabeled
Filtering and Integrating Visual Information with Motion
Lyn Bartram, Colin Ware
2001· article· en· University of New Hampshire Scholars Repository (University of New Hampshire at Manchester)· Computer Science
machine prediction:candidate · noneconsensus · none
13
citations
affunlabeled
Using Clustering to Personalize Visualization
Mohamed Mouine, Guy Lapalme
2012· article· en· 2012 16th International Conference on Information Visualisation· Computer Science
machine prediction:candidate · noneconsensus · none
13
citations
affunlabeled
KymographBuilder: Release 1.2.4
Hadrien Mary, Curtis Rueden, Tiago Ferreira
2016· article· en· Zenodo (CERN European Organization for Nuclear Research)· Computer Science
machine prediction:candidate · noneconsensus · none
12
citations
affno abstractunlabeled
The geometry and dynamics of binary trees
T. David, Thomas van Kempen, Huaxiong Huang, Phillip L. Wilson
2010· article· en· Mathematics and Computers in Simulation· Computer Science
machine prediction:candidate · noneconsensus · none
12
citations
affunlabeled
Graph Drawing and Network Visualization
Emilio Di Giacomo, Anna Lubiw
2015· book· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
12
citations
afffundunlabeled
Fluid Views
Marian Dörk, Sheelagh Carpendale, Carey Williamson
2012· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
12
citations
affunlabeled
Developing a visual taxonomy: Children's views on aesthetics
Andrew Large, Jamshid Beheshti, Nahid Tabatabaei, Valerie Nesset
2009· article· en· Journal of the American Society for Information Science and Technology· Computer Science
machine prediction:candidate · noneconsensus · none
12
citations
affunlabeled
Visual Data Mining of Web Navigational Data
Tong Zheng, William Thorne, Osmar R. Zai͏̈ane, Randy Goebel
2007· article· en· Proceedings· Computer Science
machine prediction:candidate · noneconsensus · none
12
citations
affunlabeled
Interactive Visual Analytics of Big Data
Carson K. Leung, Christopher L. Carmichael, Patrick Johnstone, Roy Ruokun Xing, David Sonny Hung-Cheung Yuen
2017· book-chapter· en· Advances in information quality and management· Computer Science
machine prediction:candidate · noneconsensus · none
12
citations
affunlabeled
Visualization Techniques for Schedule Comparison
Dandan Huang, Melanie Tory, Sheryl Staub‐French, Rachel Pottinger
2009· article· en· Computer Graphics Forum· Computer Science
machine prediction:candidate · noneconsensus · none
12
citations
afffundunlabeled
You say Potato, I say Po-Data
Tiffany Wun, Lora Oehlberg, Miriam Sturdee, Sheelagh Carpendale
2019· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
12
citations
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