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
Islamic Studies and History
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.

1,657 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.
1,657 works in the cohort · of 4,299,418page 13 of 34

Labels cover 3 of 1,657 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 1,657 of 1,657 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
The Law: how is it found?
Wael B. Hallaq
2009· book-chapter· en· Cambridge University Press eBooks· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affno abstractunlabeled
Quotes of the Quarter
2015· article· en· British Journalism Review· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affno abstractunlabeled
Quotes of the Quarter
2019· article· en· British Journalism Review· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
venueno affunlabeled
10.53762/pz61bb06
Muhammad Tahir Jaan
2000· article· en· Time to knit· Social Sciences
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
aboutno affno abstractunlabeled
Quotes of the Quarter
2006· article· en· British Journalism Review· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Sara Ahmed, Willful Subjects
Ayanna Dozier
2017· article· en· DOAJ (DOAJ: Directory of Open Access Journals)· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Women Poets Iranica
2025· paratext· en· Women Poets Iranica· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Lives of Hadith
Layla Sein
2023· article· en· Journal of Islamic and Muslim Studies· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Minor Prophets
Fred W. Guyette, Thomas Hieke, Michael W. Duggan, William J. Urbrock, Christopher T. Begg, Brian J. Meldrum
2023· article· en· Old Testament abstracts· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Major Prophets
Fred W. Guyette, Christopher T. Begg, Thomas Hieke, Juliane Eckstein, Brian J. Meldrum, Richard A. Taylor
2023· article· en· Old Testament abstracts· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affno abstractunlabeled
Quotes of the Quarter
2025· article· en· British Journalism Review· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
← previousnext →

How this was built: Screen · Findings · About