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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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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.

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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.

3,468 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.
3,468 works in the cohort · of 4,299,418page 11 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. 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.

afffundunlabeled
From run-time behavior to usage scenarios
Mohammad El‐Ramly, Eleni Stroulia, Paul Sorenson
2002· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
53
citations
affno abstractunlabeled
Software release planning for evolving systems
O. Saliu, Guenther Ruhe
2005· article· en· Innovations in Systems and Software Engineering· Computer Science
machine prediction:candidate · noneconsensus · none
53
citations
afffundno abstractunlabeled
Agile Parsing in TXL
Thomas Dean, James R. Cordy, Andrew J. Malton, Kevin A. Schneider
2003· article· en· Automated Software Engineering· Computer Science
machine prediction:candidate · noneconsensus · none
53
citations
affunlabeled
Mining Multi-level API Usage Patterns
Mohamed Aymen Saied, Omar Benomar, Hani Abdeen, Houari Sahraoui
2015· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
53
citations
affunlabeled
RETracer
Weidong Cui, Marcus Peinado, Sang Kil, Yanick Fratantonio, Vasileios P. Kemerlis
2016· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
53
citations
affno abstractunlabeled
Efficient Inference of Static Types for Java Bytecode
Étienne Gagnon, Laurie Hendren, Guillaume Marceau
2000· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
52
citations
afffundunlabeled
Automated handling of anaphoric ambiguity in requirements
Saad Ezzini, Sallam Abualhaija, Chetan Arora, Mehrdad Sabetzadeh
2022· article· en· Proceedings of the 44th International Conference on Software Engineering· Computer Science
machine prediction:candidate · noneconsensus · none
52
citations
affno abstractunlabeled
Understanding database schema evolution: A case study
Anthony Cleve, Maxime Gobert, Loup Meurice, Jerome Maes, Jens Weber
2013· article· en· Science of Computer Programming· Computer Science
machine prediction:candidate · noneconsensus · none
52
citations
affno abstractunlabeled
An empirical study of software release notes
Surafel Lemma Abebe, Nasir Ali, Ahmed E. Hassan
2015· article· en· Empirical Software Engineering· Computer Science
machine prediction:candidate · metaresearchconsensus · none
51
citations
affno abstractunlabeled
On the unreliability of bug severity data
Yuan Tian, Nasir Ali, David Lo, Ahmed E. Hassan
2015· article· en· Empirical Software Engineering· Computer Science
machine prediction:candidate · metaresearchconsensus · none
51
citations
affno abstractunlabeled
Mining trends and patterns of software vulnerabilities
Syed Shariyar Murtaza, Wael Khreich, Abdelwahab Hamou‐Lhadj, Ayşe Bener
2016· article· en· Journal of Systems and Software· Computer Science
machine prediction:candidate · noneconsensus · none
51
citations
afffundunlabeled
Dependency Smells in JavaScript Projects
Abbas Javan Jafari, Diego Elias Costa, Rabe Abdalkareem, Emad Shihab, Nikolaos Tsantalis
2021· article· en· IEEE Transactions on Software Engineering· Computer Science
machine prediction:candidate · noneconsensus · none
51
citations
afffundunlabeled
CLEVER
Mathieu Nayrolles, Abdelwahab Hamou‐Lhadj
2018· article· en· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · none
50
citations
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