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
Therapeutic Uses of Natural Elements
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.

299 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.
299 works in the cohort · of 4,299,418page 5 of 6

Labels cover 0 of 299 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 299 of 299 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.

aboutno affunlabeled
Shark Tank CBD Gummies Canada
2021· article· en· Zenodo (CERN European Organization for Nuclear Research)· Health Professions
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
aboutno affunlabeled
The Background By
2011· article· en· Health Professions
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
aboutno affunlabeled
Photograph - Tall Evergreens home
2019· other· en· Brock University Digital Repository (Brock University)· Health Professions
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
aboutno affunlabeled
Unbearable Future
2013· article· en· ScholarlyCommons (University of Pennsylvania)· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Microbiology of sands and its impact on human health
Rita Carvalho-Fonseca, Helena M. Solo‐Gabriele, Carlos Matias Dias, João Brandão
2016· article· en· European Journal of Public Health· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Elementary analysis of cosmetics: nail polishes and clays
Danielle Cristine Narloch
2021· dissertation· pt· Institutional Repository of the Federal Technological University of Paraná (RIUT) (Federal University of Technology – Paraná)· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Bonus Sample: Losing My Charisma
2023· other· en· Bulletin of Miscellaneous Information (Royal Gardens Kew)· Health Professions
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
aboutno affunlabeled
Rocher's Pond
ekcomputer
2019· dataset· en· Zenodo (CERN European Organization for Nuclear Research)· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Rocher's Pond
ekcomputer
2019· dataset· en· Zenodo (CERN European Organization for Nuclear Research)· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Common Problems of the Elderly
Karenn Chan, Lesley Charles, Jean Triscott, Bonnie Dobbs
2020· book-chapter· en· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
← previousnext →

How this was built: Screen · Findings · About