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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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Software Engineering Research
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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.

3,468 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.
3,468 works in the cohort · of 4,299,418page 30 of 70

Labels cover 10 of 3,468 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 3,468 of 3,468 works in this cohort. Predictions are machine_predicted_unvalidated teacher distillation outputs. Candidate is the union; consensus is the intersection.

affunlabeled
How heated is it?
Isabella Ferreira, Bram Adams, Jinghui Cheng
2022· preprint· en· Computer Science
distilled prediction:candidate · insufficient_payloadconsensus · none
14
citations
afffundunlabeled
Deep API learning revisited
James G. Martin, Jin Guo
2022· article· en· Computer Science
distilled prediction:candidate · noneconsensus · none
14
citations
affunlabeled
Perception-Based Software Release Planning
Mubarak Alrashoud, Abdolreza Abhari
2014· article· en· Intelligent Automation & Soft Computing· Computer Science
distilled prediction:candidate · metaepi_narrowconsensus · none
14
citations
affunlabeled
Build system maintenance
Shane McIntosh
2011· article· en· Computer Science
distilled prediction:candidate · noneconsensus · none
13
citations
affno abstractunlabeled
How to Build a Recommendation System for Software Engineering
Sebastian Proksch, Veronika Bauer, Gail C. Murphy
2015· book-chapter· en· Lecture notes in computer science· Computer Science
distilled prediction:candidate · metaepi_narrow+scholarly_communicationconsensus · none
13
citations
affunlabeled
Semantic Code Refactoring for Abstract Data Types
Shankara Pailoor, Yuepeng Wang, Işıl Dillig
2024· article· en· Proceedings of the ACM on Programming Languages· Computer Science
distilled prediction:candidate · noneconsensus · none
13
citations
affno abstractunlabeled
BigCloneBench
Jeffrey Svajlenko, Chanchal K. Roy
2021· book-chapter· de· Computer Science
distilled prediction:candidate · metaepi_narrow+insufficient_payloadconsensus · insufficient_payload
13
citations
affunlabeled
Dependency Update Strategies and Package Characteristics
Abbas Javan Jafari, Diego Elias Costa, Emad Shihab, Rabe Abdalkareem
2023· article· en· ACM Transactions on Software Engineering and Methodology· Computer Science
distilled prediction:candidate · noneconsensus · none
13
citations
affunlabeled
Detecting inefficient API usage
David Kawrykow, Martin P. Robillard
2009· article· en· Computer Science
distilled prediction:candidate · noneconsensus · none
13
citations

How this was built: Screen · Findings · About