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
Cell Image Analysis Techniques
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.

3,696 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.
3,696 works in the cohort · of 4,299,418page 50 of 74

Labels cover 7 of 3,696 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 3,696 of 3,696 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
pheno-sim: pheno-sim v1.1
Megan Fass, Kieran Kitchener
2016· article· en· Zenodo (CERN European Organization for Nuclear Research)· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
0
citations
venueno affno abstractunlabeled
Real World Imaging Data: Opportunities and Challenges (Preprint)
Jie Wu, Aline Lütz de Araújo, Sean Khozin, Merel Huisman, Domenico Mastrodicasa, Martin J. Willemink
2025· article· en· JMIR Medical Informatics· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
0
citations
affaboutunlabeled
Analysis of Huntingtin BioID Datasets 2019/04/09
Rachel Harding, Geoff Hesketh, C.H. Arrowsmith, A.M. Edwards
2019· dataset· en· Figshare· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Partial pressure (or fugacity) of carbon dioxide, water temperature, salinity and other variables collected from Submersible Autonomous Moored Instrument for CO2 (SAMI-CO2) deployed in the Labrador Sea, from 2004-06-12 to 2004-08-25 (NCEI Accession 0265462)
2022· dataset· en· National Oceanic and Atmospheric Administration (NOAA) National Centers for Environmental Information (NCEI)· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Huntingtin Construct Design For Bioid 2018/04/02
Rachel Harding, C.H. Arrowsmith, A.M. Edwards
2018· dataset· en· Zenodo (CERN European Organization for Nuclear Research)· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
0
citations
← previousnext →

How this was built: Screen · Findings · About