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
Topic
Advanced Statistical Methods and Models
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.

1,193 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.
1,193 works in the cohort · of 4,299,418page 21 of 24

Labels cover 6 of 1,193 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 1,193 of 1,193 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
Multicollinearity
Sayed A. Hussain
2015· other· en· Wiley Encyclopedia of Management· Mathematics
machine prediction:candidate · noneconsensus · none
0
citations
fundno affgpt · no categorygrok · no categoryopus · no categorymodels split
On factor copula-based mixed regression models
Pavel Krupskii, Bouchra Nasri, Bruno Rémillard
2023· preprint· en· arXiv (Cornell University)· Mathematics
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
A model selection method for S-estimation
Arie Preminger, Shinichi Sakata
2005· preprint· en· RePEc: Research Papers in Economics· Mathematics
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Scan Statistics
Reda Alhajj, Jon Rokne
2018· book-chapter· en· Mathematics
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Quasi‐Likelihood and its Extensions
S. R. Paul
2019· other· en· Wiley StatsRef: Statistics Reference Online· Mathematics
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
False Negative Rate
Stephen D. Walter
2014· other· en· Wiley StatsRef: Statistics Reference Online· Mathematics
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
One-Sample and Two-Sample Problems
Mayer Alvo, Philip L. H. Yu
2018· book-chapter· en· Springer series in the data sciences· Mathematics
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Regression
Mohammad Ali Ahmadi
2024· book-chapter· en· Elsevier eBooks· Mathematics
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
afffundunlabeled
Lower Bounds for Computing Statistical Depth
Greg Aloupis, Carmen Cortés, Francisco Gómez, Michael Soss, Godfried Toussaint
2002· article· en· idUS (Universidad de Sevilla)· Mathematics
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Bivariate Statistics with Two Continuous Variables
Daniel Stockemer, Jean‐Nicolas Bordeleau
2023· book-chapter· en· Springer texts in political science and international relations· Mathematics
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Errors in Variables
Janet Raboud
2005· other· en· Encyclopedia of Biostatistics· Mathematics
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
kujaku11/mth5: v0.3.0
2022· other· en· Zenodo (CERN European Organization for Nuclear Research)· Mathematics
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
afffundunlabeled
Robust Boosting for Regression Problems
Xiaomeng Ju, Matías Salibián‐Barrera
2020· preprint· en· arXiv (Cornell University)· Mathematics
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Approximate Data Depth Revisited
Rasoul Shahsavarifar, David Avis
2018· article· en· arXiv (Cornell University)· Mathematics
machine prediction:candidate · noneconsensus · none
0
citations
← previousnext →

How this was built: Screen · Findings · About