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
Statistical Methods and Inference
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.

1,935 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.
1,935 works in the cohort · of 4,299,418page 3 of 39

Labels cover 22 of 1,935 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 1,935 of 1,935 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.

affunlabeled
QUASI-CONCAVE DENSITY ESTIMATION
Roger Koenker, Ivan Mizera
2013· article· en· Mathematics
machine prediction:candidate · noneconsensus · none
68
citations
venueaboutno affunlabeled
Constrained penalized splines
Mary C. Meyer
2012· article· en· Canadian Journal of Statistics· Mathematics
machine prediction:candidate · noneconsensus · none
59
citations
affunlabeled
Censoring Unbiased Regression Trees and Ensembles
Jon A. Steingrimsson, Liqun Diao, Robert L. Strawderman
2018· article· en· Journal of the American Statistical Association· Mathematics
machine prediction:candidate · noneconsensus · none
58
citations
aboutno affunlabeled
The functional linear array model
Sarah Brockhaus, Fabian Scheipl, Torsten Hothorn, Sonja Greven
2015· article· en· Statistical Modelling· Mathematics
machine prediction:candidate · noneconsensus · none
54
citations
affunlabeled
Principal Component Analysis for Big Data
Jianqing Fan, Qiang Sun, Wen‐Xin Zhou, Ziwei Zhu
2018· other· en· Wiley StatsRef: Statistics Reference Online· Mathematics
machine prediction:candidate · noneconsensus · none
53
citations
affunlabeled
Testing functional inequalities
Sokbae Lee, Kyungchui Song, Yoon‐Jae Whang
2017· report· en· Mathematics
machine prediction:candidate · noneconsensus · none
51
citations
fundno affno abstractunlabeled
Multivariate nonparametric test of independence
Yanan Fan, Pierre Lafaye de Micheaux, Spiridon Penev, Donna Salopek
2016· article· en· Journal of Multivariate Analysis· Mathematics
machine prediction:candidate · noneconsensus · none
50
citations

How this was built: Screen · Findings · About