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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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Cloud Computing and Resource Management
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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.

1,591 results · 1 filter active ·
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20002025
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Machine labels · sparse coverage
Evidence
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An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
1,591 works in the cohort · of 4,299,418page 26 of 32

Labels cover 1 of 1,591 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 1,591 of 1,591 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
TinySQL
2009· book-chapter· ja· Encyclopedia of Database Systems· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
venueno affno abstractunlabeled
10.1016/s1541-9800(06)71322-9
2000· article· en· Time to knit· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
affunlabeled
Large-scale multilevel streaming data analytics
Farhana Zulkernine, Haruna Isah, Sidney Givigi, Yan Liu, Edward Shim, Marwa Elsayed
2018· article· en· Computer Science and Software Engineering· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
speckleworks/SpeckleCore 1.6.16-wip
2019· other· en· Zenodo (CERN European Organization for Nuclear Research)· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Call for Papers, Issue 1/2024
Jerry Chun‐Wei Lin, Gautam Srivastava, Yudong Zhang, Christoph M. Flath
2022· paratext· en· Business & Information Systems Engineering· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
affunlabeled
SLA for Sequential Serverless Chains
Mohamed Elsakhawy, Michael Bauer
2021· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
SQL Server Rises to the Clouds
Bob Ward
2020· book-chapter· en· Apress eBooks· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
UV-CDAT 2.2.0
D. N. Williams, Aashish Chaudhary, Thomas W Maxwell, David Lonie, Paul J. Durack, Chris Harris +15 more
2015· article· en· Zenodo (CERN European Organization for Nuclear Research)· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Energy Management for Cyber-Physical Cloud Systems
Neeraj Kumar, Athanasios V. Vasilakos, Kim‐Kwang Raymond Choo, Laurence T. Yang
2020· article· en· Future Generation Computer Systems· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Randomized load balancing with a helper
Chunpu Wang, Chen Feng, Julian Cheng
2017· article· en· IEEE Conference Proceedings· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
The GENI Experiment Engine
Andy Bavier, Jim Hao Chen, Joe Mambretti, Rick McGeer, Sean McGeer, Jude Nelson +4 more
2014· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Cloud Computing and Adult Literacy.
Griff Richards, Rory McGreal, Brian Stewart, Matthias Stürm
2014· article· en· IEEE International Conference on Cloud Computing Technology and Science· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Taming services for IBM cloud.
Nazim H. Madhavji, John Steinbacher, Andriy Miranskyy, Tony Erwin, A. Ibrahim, Priyanka Prakash Naikade +3 more
2019· article· en· Conference of the Centre for Advanced Studies on Collaborative Research· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Example Data for pyOpenMS
Hannes Röst
2019· dataset· en· Figshare· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations

How this was built: Screen · Findings · About