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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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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
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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.

1,099 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.
1,099 works in the cohort · of 4,299,418page 8 of 22

Labels cover 1 of 1,099 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 1,099 of 1,099 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.

affunlabeled
Predicting Web Service Response Time Percentiles
Yasaman Amannejad, Diwakar Krishnamurthy, Behrouz H. Far
2016· article· en· Conference on Network and Service Management· Computer Science
machine prediction:candidate · noneconsensus · none
6
citations
affunlabeled
Threat Hunting in Windows Using Big Security Log Data
Mohammad Rasool Fatemi, Ali A. Ghorbani
2019· book-chapter· en· Advances in information security, privacy, and ethics book series· Computer Science
machine prediction:candidate · noneconsensus · none
6
citations
affunlabeled
Visualizing the Results of Field Testing
Brian Chan, Ying Zou, Ahmed E. Hassan, Anand Sinha
2010· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
6
citations
afffundunlabeled
Evaluation of Implement Monitoring Systems
Aadesh Kumar Rakhra, Danny Mann
2013· article· en· Journal of Agricultural Safety and Health· Computer Science
machine prediction:candidate · noneconsensus · none
6
citations
affunlabeled
Network in a box
François Gagnon, Babak Esfandiari, Tomas Dej
2010· article· en· International Conference on Data Communication Networking· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · none
5
citations
affunlabeled
ShellFusion
Neng Zhang, Chao Liu, Xin Xia, Christoph Treude, Ying Zou, David Lo +1 more
2022· article· en· Proceedings of the 44th International Conference on Software Engineering· Computer Science
machine prediction:candidate · noneconsensus · none
5
citations
affunlabeled
Execution mining
Geoffrey Lefebvre, Brendan Cully, Christopher C. D. Head, Mark Spear, N.C. Hutchinson, Mike Feeley +1 more
2012· article· en· ACM SIGPLAN Notices· Computer Science
machine prediction:candidate · noneconsensus · none
5
citations
affunlabeled
BAP
Jerry Rolia, Diwkar Krishnamurthy, Giuliano Casale, Stephen Dawson
2010· article· en· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · none
5
citations
affvenueunlabeled
The scalability of AspectJ
Arjun Singh, Gregor Kiczales
2007· article· en· Proceedings of CASCON· Computer Science
machine prediction:candidate · noneconsensus · none
5
citations
affno abstractunlabeled
A unit test approach for database schema evolution
Katarina Grolinger, Miriam A. M. Capretz
2010· article· en· Information and Software Technology· Computer Science
machine prediction:candidate · noneconsensus · none
5
citations

How this was built: Screen · Findings · About