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 38 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 teacher distillation outputs. Candidate is the union; consensus is the intersection.

affunlabeled
Mixed Data Kernel Copulas
Jeffrey S. Racine
2013· preprint· en· RePEc: Research Papers in Economics· Mathematics
distilled prediction:candidate · metaresearch+metaepi_narrow+research_integrity+insufficient_payloadconsensus · none
0
citations
affunlabeled
Wild Bootstrap Tests for IV Regression
Russell Davidson, James G. MacKinnon
2008· preprint· en· AgEcon Search (University of Minnesota, USA)· Mathematics
distilled prediction:candidate · metaepi_narrowconsensus · none
0
citations
affunlabeled
Mixed Effects Random Forest for Clustered Data
Ahlem Hajjem, François Bellavance, Denis Larocque
2010· article· fr· Les Cahiers du GERAD· Mathematics
distilled prediction:candidate · metaresearch+metaepi_narrowconsensus · none
0
citations
affno abstractunlabeled
Nonparametric Models with Random Effects
Yiguo Sun, Wei Lin, Qi Li
2017· book-chapter· en· Advanced studies in theoretical and applied econometrics· Mathematics
distilled prediction:candidate · metaepi_narrowconsensus · none
0
citations
venueno affunlabeled
Olsavs: A New Algorithm For Model Selection
Nicklaus T. Hicks, Hasthika S. Rupasinghe Arachchige Don
2023· article· en· International Journal of Statistics and Probability· Mathematics
distilled prediction:candidate · noneconsensus · none
0
citations
fundno affunlabeled
A test of singularity for distribution functions
Victoria Zinde‐Walsh, John W. Galbraith
2011· preprint· en· RePEc: Research Papers in Economics· Mathematics
distilled prediction:candidate · metaresearchconsensus · none
0
citations
venueno affunlabeled
10.51847/a7p5z0Lwpk
2000· article· en· Time to knit· Mathematics
distilled prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
afffundunlabeled
Empirical Likelihood Block Bootstrapping
Jason Allen, Allan W. Gregory, Katsumi Shimotsu
2008· preprint· en· Econstor (Econstor)· Mathematics
distilled prediction:candidate · metaepi_narrow+research_integrity+insufficient_payloadconsensus · none
0
citations
affunlabeled
Tree-based boosting with functional data
Xiaomeng Ju, Matías Salibián‐Barrera
2021· preprint· en· arXiv (Cornell University)· Mathematics
distilled prediction:candidate · metaepi_narrowconsensus · none
0
citations
affunlabeled
Two-sample high-dimensional empirical likelihood
Jianglin Fang, Wanrong Liu, Xuewen Lu
2017· article· en· Communication in Statistics- Theory and Methods· Mathematics
distilled prediction:candidate · metaresearchconsensus · none
0
citations
affunlabeled
On Improved Shrinkage Estimators for Concave Loss
Tatsuya Kubokawa, Éric Marchand, William E. Strawderman
2014· preprint· en· RePEc: Research Papers in Economics· Mathematics
distilled prediction:candidate · metaresearch+metaepi_narrowconsensus · none
0
citations
affunlabeled
Conditional Variance Function Estimation
Jeffrey S. Racine
2018· book-chapter· en· Cambridge University Press eBooks· Mathematics
distilled prediction:candidate · metaepi_narrowconsensus · none
0
citations

How this was built: Screen · Findings · About