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
Year range
Sort
Language
Type
Field
Venue
Topic
Privacy-Preserving Technologies in Data
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.

1,809 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.
1,809 works in the cohort · of 4,299,418page 4 of 37

Labels cover 7 of 1,809 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 1,809 of 1,809 works in this cohort. Predictions are machine_predicted_unvalidated teacher distillation outputs. Candidate is the union; consensus is the intersection.

afffundunlabeled
Estimation Efficiency Under Privacy Constraints
2018· article· en· IEEE Transactions on Information Theory· Computer Science
distilled prediction:candidate · open_science+insufficient_payloadconsensus · none
64
citations
affno abstractunlabeled
Privacy-preserving boosting
2007· article· en· Data Mining and Knowledge Discovery· Computer Science
distilled prediction:candidate · metaresearch+open_scienceconsensus · open_science
60
citations
affno abstractunlabeled
Publishing anonymous survey rating data
2010· article· en· Data Mining and Knowledge Discovery· Computer Science
distilled prediction:candidate · metaresearch+scholarly_communication+open_scienceconsensus · scholarly_communication+open_science
56
citations
affunlabeled
Notes on information-theoretic privacy
2014· article· en· Computer Science
distilled prediction:candidate · metaresearch+open_science+insufficient_payloadconsensus · open_science
55
citations
affunlabeled
Differential Privacy Models for Location- Based Services
2016· preprint· en· HAL (Le Centre pour la Communication Scientifique Directe)· Computer Science
distilled prediction:candidate · metaresearch+metaepi_narrow+scholarly_communication+open_scienceconsensus · open_science
53
citations
affunlabeled
SAQE
2020· article· en· Proceedings of the VLDB Endowment· Computer Science
distilled prediction:candidate · open_scienceconsensus · open_science
53
citations
affunlabeled
Asynchronous Federated Unlearning
2023· article· en· Computer Science
distilled prediction:candidate · metaresearch+open_science+insufficient_payloadconsensus · open_science
51
citations
afffundno abstractunlabeled
Anonymizing trajectory data for passenger flow analysis
2014· article· en· Transportation Research Part C Emerging Technologies· Computer Science
distilled prediction:candidate · metaresearch+metaepi_narrow+open_scienceconsensus · open_science
50
citations
affunlabeled
Synthetic Data for Social Good
2017· preprint· en· arXiv (Cornell University)· Computer Science
distilled prediction:candidate · metaresearch+metaepi_narrow+open_scienceconsensus · open_science
50
citations

How this was built: Screen · Findings · About