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
Complexity and Algorithms in Graphs
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.

755 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.
755 works in the cohort · of 4,299,418page 7 of 16

Labels cover 0 of 755 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 755 of 755 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
KRW Composition Theorems via Lifting
Susanna F. de Rezende, Or Meir, Jakob Nordstr”öm, Toniann Pitassi, Robert Robere
2020· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
6
citations
affunlabeled
Estimating parameters associated with monotone properties
Carlos Hoppen, Yoshiharu Kohayakawa, Richard Lang, Hanno Lefmann, Henrique Stagni
2020· article· en· Combinatorics Probability Computing· Computer Science
machine prediction:candidate · noneconsensus · none
6
citations
affunlabeled
The optimal path-matching problem
William H. Cunningham, Jim Geelen
2002· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
6
citations
affno abstractunlabeled
Lower Bounds against Weakly Uniform Circuits
Ruiwen Chen, Valentine Kabanets
2012· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
6
citations
affno abstractunlabeled
Lift-and-Project Methods for Set Cover and Knapsack
Eden Chlamtáč, Zachary Friggstad, Konstantinos Georgiou
2013· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
6
citations
affunlabeled
Guest Column
Susanna F. de Rezende, Mika Göös, Robert Robere
2022· article· en· ACM SIGACT News· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · none
6
citations
fundno affunlabeled
[no title]
Yuval Dagan, Hamed Hatami, Yaqiao Li
2018· article· en· Theory of Computing· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · none
5
citations
affno abstractunlabeled
On the monotonicity of a data stream
Funda Ergün, Hossein Jowhari
2014· article· en· COMBINATORICA· Computer Science
machine prediction:candidate · noneconsensus · none
5
citations
afffundno abstractunlabeled
The Landscape of Communication Complexity Classes
Mika Göös, Toniann Pitassi, Thomas Watson
2018· article· en· Computational Complexity· Computer Science
machine prediction:candidate · noneconsensus · none
5
citations
afffundunlabeled
Sparsification of Decomposable Submodular Functions
Akbar Rafiey, Yuichi Yoshida
2022· article· en· Proceedings of the AAAI Conference on Artificial Intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
5
citations
affunlabeled
A Composition Theorem for Conical Juntas.
Mika Göös, T. S. Jayram
2015· article· en· DROPS (Schloss Dagstuhl – Leibniz Center for Informatics)· Computer Science
machine prediction:candidate · noneconsensus · none
5
citations
affno abstractunlabeled
Efficiency of Local Search
Andreĭ A. Bulatov, Evgeny Skvortsov
2006· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
5
citations
← previousnext →

How this was built: Screen · Findings · About