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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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Advanced Software Engineering Methodologies
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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.

1,299 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.
1,299 works in the cohort · of 4,299,418page 14 of 26

Labels cover 1 of 1,299 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 1,299 of 1,299 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
Using UML scenarios in B2B systems
Abdeslam Jakimi, Ayoub Sabraoui, Aziz Salah, M. El Koutbi
2008· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
5
citations
affunlabeled
Merging Features in Featured Transition Systems
Joanne M. Atlee, Sandy Beidu, Uli Fahrenberg, Axel Legay
2015· preprint· en· UWSpace (University of Waterloo)· Computer Science
machine prediction:candidate · noneconsensus · none
5
citations
affunlabeled
AspectAda
Knut H. Pedersen, Constantinos Constantinides
2005· article· en· ACM SIGAda Ada Letters· Computer Science
machine prediction:candidate · noneconsensus · none
5
citations
affno abstractunlabeled
An Automated Change Impact Analysis Approach to GRL Models
Hasan Salim Alkaf, Jameleddine Hassine, Abdelwahab Hamou‐Lhadj, Luay Alawneh
2017· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
5
citations
affunlabeled
Reference Architecture Design: A Practical Approach
Mustapha Derras, Laurent Deruelle, Jean Michel Douin, Nicole Lévy, Francisca Losavio, Yann Pollet +1 more
2018· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
5
citations
affno abstractunlabeled
Runtime Verification for the Web
Sylvain Hallé, Roger Villemaire
2010· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
5
citations
affunlabeled
Coordination of Independent Loops in Self-Adaptive Systems
Jacopo Panerati, Martina Maggio, Matteo Carminati, Filippo Sironi, Marco Triverio, Marco D. Santambrogio
2014· article· en· ACM Transactions on Reconfigurable Technology and Systems· Computer Science
machine prediction:candidate · noneconsensus · none
5
citations
affunlabeled
Prolonging the Aging of Software Systems
Constantinos Constantinides, Venera Arnaoudova
2009· book-chapter· en· IGI Global eBooks· Computer Science
machine prediction:candidate · noneconsensus · none
5
citations

How this was built: Screen · Findings · About