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
Image Retrieval and Classification 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.

1,015 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.
1,015 works in the cohort · of 4,299,418page 9 of 21

Labels cover 2 of 1,015 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 1,015 of 1,015 works in this cohort. Predictions are machine_predicted_unvalidated teacher distillation outputs. Candidate is the union; consensus is the intersection.

affno abstractunlabeled
Concept-Based Retrieval of Art Documents
Jose A. Lay, Ling Guan
2003· book-chapter· en· Lecture notes in computer science· Computer Science
distilled prediction:candidate · metaepi_narrowconsensus · none
6
citations
affno abstractunlabeled
Feature Extraction and Selection Methods
Krzysztof J. Cios, Roman W. Świniarski, Witold Pedrycz, Lukasz Kurgan
2007· book-chapter· en· Computer Science
distilled prediction:candidate · noneconsensus · none
6
citations
afffundunlabeled
Force histograms computed in O(NlogN)
Jingbo Ni, Pascal Matsakis
2008· article· en· Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition· Computer Science
distilled prediction:candidate · metaepi_narrow+scholarly_communication+insufficient_payloadconsensus · insufficient_payload
6
citations
affunlabeled
Report on MDM/KDD2000
Simeon Simoff, Osmar R. Zai͏̈ane
2000· article· en· ACM SIGKDD Explorations Newsletter· Computer Science
distilled prediction:candidate · insufficient_payloadconsensus · none
6
citations
affunlabeled
Visual Object Discovery
Pawan Sinha, Benjamin Balas, Yuri Ostrovsky, Jonas Wulff
2009· book-chapter· en· Cambridge University Press eBooks· Computer Science
distilled prediction:candidate · metaepi_narrowconsensus · none
6
citations
affunlabeled
Communicating Image Content
Lisa Tang, Jenny Carter
2011· article· en· Proceedings of the Human Factors and Ergonomics Society Annual Meeting· Computer Science
distilled prediction:candidate · noneconsensus · none
5
citations
affno abstractunlabeled
Foundation of the DISIMA Image Query Languages
Vincent Oria, M. TAMER ÖZSU, Paul Iglinski
2004· article· en· Multimedia Tools and Applications· Computer Science
distilled prediction:candidate · noneconsensus · none
5
citations

How this was built: Screen · Findings · About