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
Springer optimization and its applications
Topic
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.

31 results · 1 filter active ·
Results by year
20062025
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.
31 works in the cohort · of 4,299,418page 1 of 1

Labels cover 0 of 31 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 31 of 31 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
Large Sets Avoiding Rough Patterns
Jacob Denson, Malabika Pramanik, Joshua Zahl
2020· book-chapter· en· Springer optimization and its applications· Mathematics
machine prediction:candidate · noneconsensus · none
10
citations
affno abstractunlabeled
Dynamics of Disasters
Ilias Kotsireas, Anna Nagurney, Pãnos M. Pardalos
2021· book· en· Springer optimization and its applications· Social Sciences
machine prediction:candidate · noneconsensus · none
9
citations
affno abstractunlabeled
Variable Neighborhood Search
Dragan Urošević, Raca Todosijević, Nenad Mladenović, Jack Brimberg
2023· book-chapter· en· Springer optimization and its applications· Engineering
machine prediction:candidate · noneconsensus · none
4
citations
affno abstractunlabeled
Generating Eigenvalue Bounds Using Optimization
Henry Wolkowicz
2009· book-chapter· en· Springer optimization and its applications· Computer Science
machine prediction:candidate · noneconsensus · none
4
citations
affno abstractunlabeled
Modeling of Technological Change
Natali Hritonenko, Yuri Yatsenko
2013· book-chapter· en· Springer optimization and its applications· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
4
citations
affno abstractunlabeled
Multivariable Calculus
A. M. Mathai, H. J. Haubold
2017· book-chapter· en· Springer optimization and its applications· Computer Science
machine prediction:candidate · noneconsensus · none
3
citations
affno abstractunlabeled
Asymmetries in Competitive Location Models on the Line
H. A. Eiselt, Vladimir Marianov
2017· book-chapter· en· Springer optimization and its applications· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
2
citations
afffundno abstractunlabeled
On Two Inequalities for Polynomials in the Unit Disk
Richard Fournier, Stephan Ruscheweyh
2017· book-chapter· en· Springer optimization and its applications· Mathematics
machine prediction:candidate · noneconsensus · none
2
citations
affno abstractunlabeled
Geometrical Analysis of Solutions
Jorge Mortes, F. Parreño, Rafael Martı́
2023· book-chapter· en· Springer optimization and its applications· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
1
citations
affno abstractunlabeled
Less Is More Approach
Raca Todosijević, Dragan Urošević, Nenad Mladenović, Jack Brimberg
2023· book-chapter· en· Springer optimization and its applications· Computer Science
machine prediction:candidate · noneconsensus · none
1
citations
affno abstractunlabeled
Scalar and Asymptotic Scalar Derivatives
2008· book· en· Springer optimization and its applications· Physics and Astronomy
machine prediction:candidate · noneconsensus · none
1
citations
affno abstractunlabeled
Scalar Derivatives in Hilbert Spaces
G. Isac, S. Z. Németh
2008· book-chapter· en· Springer optimization and its applications· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Scalar Derivatives in Banach Spaces
G. Isac, S. Z. Németh
2008· book-chapter· en· Springer optimization and its applications· Mathematics
machine prediction:candidate · noneconsensus · none
0
citations

How this was built: Screen · Findings · About