MétaCan
ENFR
Menu
Cohort builder

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.

Export CSVExport JSONAPI query

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.

Search term
Author
Year range
→
Sort
Language
Type
Field
Venue
Topic
Model-Driven Software Engineering Techniques
Retraction
Abstract
Evidence source
Study design
Label agreement
Label status

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.

695 results · 1 filter active ·
Results by year
20002025
Publication date
Categories
Machine labels · sparse coverage
Evidence
Language
Type
Citations
An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
695 works in the cohort · of 4,299,418page 12 of 14

Labels cover 3 of 695 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 695 of 695 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.

fundno affunlabeled
Virtual Frameworks for Source Migration
2006· dissertation· en· UWSpace (University of Waterloo)· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
[no title]
Simon Van Mierlo, Erwan Bousse, Hans Vangheluwe, Manuel Wimmer, Clark Verbrugge, Martin Gogolla +2 more
2017· preprint· en· Anet (University of Antwerp)· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
venueno affunlabeled
CAML Milestones
2023· article· fr· CAML Review / Revue de l ACBM· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
venueno affunlabeled
A Novel Method for Refactoring UML Metamodel
Berraouna Abdelkader
2023· article· en· Ingénierie des systèmes d information· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Towards a Body of Knowledge for Model-Based Software Engineering
Federico Ciccozzi, Michalis Famelis, Gerti Kappel, Leen Lambers, Sébastien Mosser, Richard F. Paige +6 more
2018· article· en· HAL (Le Centre pour la Communication Scientifique Directe)· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
UML crisis! An educational perspective
Zheng; id_orcid 0000-0002-9704-7651 Li, Aidan McGowan, Yan Liu, Abdelwahab Hamou-Lhadj
2025· article· en· Research Portal (Queen's University Belfast)· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Quantools: A MDA transformation approach
Paulo Lumertz, Ana Paula Terra Bacelo, Toacy Oliveira
2010· article· en· Revista de Informática Teórica e Aplicada· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Towards an Assessment Grid for Intelligent Modeling Assistance
Benoît Combemale, Silvia Abrahão, Nelly Bencomo, Loli Burgueño, Gregor Engels, Jörg Kienzle +3 more
2020· article· en· HAL (Le Centre pour la Communication Scientifique Directe)· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
VDesign A Formal Modeling and Optimization Software
Jean Bigeon, Emmanuel Bigeon, E. Atienza
2018· preprint· en· HAL (Le Centre pour la Communication Scientifique Directe)· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Eating our own dog food
James R. Cordy
2009· article· en· ACM SIGPLAN Notices· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Model-Driven AI for Games: Research Plan
Christopher Dragert
2012· article· en· Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Use Cases in the UML
Brian Dobing, Jeffrey Parsons
2009· book-chapter· en· IGI Global eBooks· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Generation Rules in POMA Architecture
Mohamed Taleb, Ahmed Seffah, Alain Abran
2010· article· en· Journal of Software Engineering and Applications· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Embracing Automation for Monograph Acquisition
Denise Koufogiannakis
2021· article· en· Against the grain· Computer Science
machine prediction:candidate · scholarly_communicationconsensus · none
0
citations
affno abstractunlabeled
Extending instance-based and linear models
Ian H. Witten, Eibe Frank, Mark A. Hall, Christopher Pal, James R. Foulds
2025· book-chapter· en· Elsevier eBooks· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
MBSA Model-Exchange and Its Challenges
Tony Ghueldre, Wilkinson Joas, Julien Vidalie, Xavier De Bossoreille, Sébastien Duthoit
2025· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
A cross-technology benchmark for incremental graph queries
Georg Hinkel, Antonio García‐Domínguez, René Schöne, Artur Boronat, Massimo Tisi, Théo Le Calvar +6 more
2021· article· en· Software & Systems Modeling· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
← previousnext →

How this was built: Screen · Findings · About