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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 Testing and Debugging Techniques
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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.

996 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.
996 works in the cohort · of 4,299,418page 8 of 20

Labels cover 2 of 996 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 996 of 996 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
Automatically Repairing Concurrency Bugs with ARC
David Kelk, Kevin Jalbert, Jeremy S. Bradbury
2013· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
11
citations
affunlabeled
Transformation by example
Houari Sahraoui, Mounir Boukadoum, Marouane Kessentini
2010· dissertation· en· Computer Science
machine prediction:candidate · noneconsensus · none
10
citations
afffundunlabeled
Data-Driven Mutation Analysis for Cyber-Physical Systems
Enrico Viganò, Oscar Cornejo, Fabrizio Pastore, Lionel Briand
2022· article· en· IEEE Transactions on Software Engineering· Computer Science
machine prediction:candidate · noneconsensus · none
10
citations
afffundunlabeled
: Priority Aware Test Case Reduction
Golnaz Gharachorlu, William N. Sumner
2019· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
10
citations
affunlabeled
Synthesizing iterators from abstraction functions
Derek Rayside, Vajihollah Montaghami, Francesca Leung, Albert Yuen, Kevin Xu, Daniel Jackson
2012· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
10
citations
affno abstractunlabeled
Multiplexing of Partially Ordered Events
Colin Campbell, Margus Veanes, Jiale Huo, Alexandre Petrenko
2005· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
10
citations
affunlabeled
The robotics experience
Gregory S. Broten, David Mackay, Simon P. Monckton, Jack Collier
2009· article· en· IEEE Robotics & Automation Magazine· Computer Science
machine prediction:candidate · noneconsensus · none
9
citations
affno abstractunlabeled
An Evaluation of Auto-Scoping in OpenMP
Michael Voss, Eric S. Y. Chiu, Patrick Man Yan Chow, Catherine Wong, Kevin C.J. Yuen
2005· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
9
citations
affno abstractgemma · no categorygpt · no categorymodels split
Divide-by-Zero Exception Raising via Branch Coverage
Neelesh Bhattacharya, Abdelilah Sakti, Giuliano Antoniol, Yann‐Gaël Guéhéneuc, Gilles Pesant
2011· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
9
citations
affno abstractunlabeled
On testing machine learning programs
Houssem Ben Braiek, Foutse Khomh
2020· preprint· en· Journal of Systems and Software· Computer Science
machine prediction:candidate · noneconsensus · none
9
citations

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