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
Computational Physics and Python Applications
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.

1,060 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.
1,060 works in the cohort · of 4,299,418page 4 of 22

Labels cover 4 of 1,060 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 1,060 of 1,060 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
Creating and Viewing HTML Files with Python
William J. Turkel, Adam Crymble
2012· article· en· The Programming Historian· Computer Science
machine prediction:candidate · noneconsensus · none
1
citations
venueno affunlabeled
The Physical Nature of Velocity
Zhonggang Li
2018· article· en· Applied Physics Research· Computer Science
machine prediction:candidate · noneconsensus · none
1
citations
affaboutunlabeled
Observations of the Crab Nebula and Pulsar with STACEE
J. Kildea, J. Ball, D. Bramel, J. Carson, C. E. Covault, D. D. Driscoll +12 more
2005· article· en· CERN Document Server (European Organization for Nuclear Research)· Computer Science
machine prediction:candidate · noneconsensus · none
1
citations
affvenueaboutunlabeled
Improvements in Transport Phenomena Teaching
Pierre Proulx, Francis B. Lavoie
2018· article· en· Proceedings of the Canadian Engineering Education Association (CEEA)· Computer Science
machine prediction:candidate · noneconsensus · none
1
citations
aboutno affunlabeled
Superresolved HYDI dataset
Eleftherios Garyfallidis, E Nahla, Yu-Chien Wu
2019· dataset· en· Figshare· Computer Science
machine prediction:candidate · noneconsensus · none
1
citations
fundno affno abstractunlabeled
Will machines change mathematics?
Maia Fraser, Andrew Granville, Michael Harris, Colin McLarty, Emily Riehl, Akshay Venkatesh
2024· article· en· Bulletin of the American Mathematical Society· Computer Science
machine prediction:candidate · noneconsensus · none
1
citations
venueno affno abstractunlabeled
Lawn as a site of environmental conflict
2000· other· en· Library and Archives Canada (Government of Canada)· Computer Science
machine prediction:candidate · noneconsensus · none
1
citations
affunlabeled
Introduction to Python's Syntax
Kinsey Church, Thaddé Rolon-Mérette, Matt Ross, Damien Rolon-Mérette
2021· article· en· The Quantitative Methods for Psychology· Computer Science
machine prediction:candidate · noneconsensus · none
1
citations
fundno affunlabeled
JPEG Inspired Deep Learning
Ahmed H. Salamah, Kaixiang Zheng, Yiwen Liu, En‐hui Yang
2024· preprint· en· arXiv (Cornell University)· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
sd_quadrature.R
Thomas E. Barchyn
2020· dataset· en· Harvard Dataverse· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
aboutno affunlabeled
Occurrence Download
2025· dataset· en· Global Biodiversity Information Facility· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
aboutno affno abstractunlabeled
canada_posttax_distribution_19631975x.tab
Timothy Jacobs Hicks
2016· dataset· en· Harvard Dataverse· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affno abstractunlabeled
Magnetotelluric Transfer Functions
2017· other· en· NSF Seismological Facility for the Advancement of Geoscience (SAGE)· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
← previousnext →

How this was built: Screen · Findings · About