MétaCan
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.

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
Formal Methods in Verification
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.

1,244 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.
1,244 works in the cohort · of 4,299,418page 1 of 25

Labels cover 3 of 1,244 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 1,244 of 1,244 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
The ASTREÉ Analyzer
Patrick Cousot, Radhia Cousot, Jérôme Ferêt, Laurent Mauborgne, Antoine Miné, David Monniaux +1 more
2005· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
392
citations
affunlabeled
Anytime Point-Based Approximations for Large POMDPs
Joëlle Pineau, Geoff Gordon, Sebastian Thrun
2006· article· en· Journal of Artificial Intelligence Research· Computer Science
machine prediction:candidate · noneconsensus · none
374
citations
affno abstractunlabeled
Metrics for labelled Markov processes
Josée Desharnais, Vineet Gupta, Radha Jagadeesan, Prakash Panangaden
2003· article· en· Theoretical Computer Science· Computer Science
machine prediction:candidate · noneconsensus · none
309
citations
affunlabeled
Labelled Markov Processes
Prakash Panangaden
2009· book· en· IMPERIAL COLLEGE PRESS eBooks· Computer Science
machine prediction:candidate · noneconsensus · none
219
citations
affno abstractunlabeled
Optimal Paths in Weighted Timed Automata
Rajeev Alur, Salvatore La Torre, George J. Pappas
2001· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
209
citations
affunlabeled
Multi-valued symbolic model-checking
Marsha Chećhik, Benet Devereux, Steve Easterbrook, Arie Gurfinkel
2003· article· en· ACM Transactions on Software Engineering and Methodology· Computer Science
machine prediction:candidate · noneconsensus · none
188
citations
affunlabeled
Points-to analysis using BDDs
Marc Berndl, Ondřej Lhoták, Feng Qian, Laurie Hendren, Navindra Umanee
2003· article· en· ACM SIGPLAN Notices· Computer Science
machine prediction:candidate · noneconsensus · none
188
citations
affno abstractunlabeled
Learning Rate Based Branching Heuristic for SAT Solvers
Liang Jia, Vijay Ganesh, Pascal Poupart, Krzysztof Czarnecki
2016· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
160
citations
affno abstractunlabeled
New directions in fuzzy automata
M. Doostfatemeh, Stefan C. Kremer
2004· article· en· International Journal of Approximate Reasoning· Computer Science
machine prediction:candidate · noneconsensus · none
149
citations
afffundunlabeled
Software model checking via large-block encoding
Dirk Beyer, Alessandro Cimatti, Alberto Griggio, M. Erkan Keremoğlu, Simon Fraser Univers, Roberto Sebastiani
2009· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
147
citations
affunlabeled
Points-to analysis using BDDs
Marc Berndl, Ondřej Lhoták, Feng Qian, Laurie Hendren, Navindra Umanee
2003· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
141
citations
affno abstractunlabeled
Multiple Valued Logic: Concepts and Representations
D. Michael Miller, Mitchell A. Thornton
2007· article· en· Synthesis lectures on digital circuits and systems· Computer Science
machine prediction:candidate · noneconsensus · none
136
citations
afffundunlabeled
General LTL Specification Mining (T)
Caroline Lemieux, Dennis Park, Ivan Beschastnikh
2015· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
134
citations
affunlabeled
Formal Verification Methods
Osman Hasan, Sofiène Tahar
2014· book-chapter· en· Advances in information quality and management· Computer Science
machine prediction:candidate · noneconsensus · none
108
citations
afffundno abstractunlabeled
Explaining counterexamples using causality
Ilan Beer, Shoham Ben-David, Hana Chockler, Avigail Orni, Richard Trefler
2011· article· en· Formal Methods in System Design· Computer Science
machine prediction:candidate · noneconsensus · none
104
citations
affunlabeled
Symbolic pointer analysis revisited
Jianwen Zhu, Silvian Calman
2004· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
101
citations
affunlabeled
Value-Directed Compression of POMDPs
Pascal Poupart, Craig Boutilier
2002· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
99
citations
affno abstractunlabeled
Exploiting the Power of mip Solvers in maxsat
Jessica Davies, Fahiem Bacchus
2013· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
92
citations
affunlabeled
Data flow testing as model checking
Hyoung Seok Hong, Sung Deok, Insup Lee, Oleg Sokolsky, Hasan Ural
2003· article· en· ScholarlyCommons (University of Pennsylvania)· Computer Science
machine prediction:candidate · noneconsensus · none
90
citations
affunlabeled
Discrete Optimization with Decision Diagrams
David Bergman, André A. Ciré, Willem‐Jan van Hoeve, J. N. Hooker
2016· article· en· INFORMS journal on computing· Computer Science
machine prediction:candidate · noneconsensus · none
88
citations
affno abstractunlabeled
Beautiful Interpolants
Aws Albarghouthi, Kenneth L. McMillan
2013· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
75
citations
affno abstractunlabeled
Explaining Counterexamples Using Causality
Ilan Beer, Shoham Ben-David, Hana Chockler, Avigail Orni, Richard Trefler
2009· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
72
citations
affno abstractunlabeled
Model-Checking Over Multi-Valued Logics
Marsha Chećhik, Steve Easterbrook, Victor Petrovykh
2001· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
69
citations

How this was built: Screen · Findings · About