MétaCan
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.

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
eLife
Topic
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.

2,170 results · 1 filter active ·
Results by year
20042025
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.
2,170 works in the cohort · of 4,299,418page 28 of 44

Labels cover 9 of 2,170 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 2,170 of 2,170 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.

afffundunlabeled
Systems genomics of salinity stress response in rice
Sonal Gupta, Maricris Zaidem, A.G. Sajise, Irina Ćalić, Mignon A. Natividad, Georgina V. Vergara +5 more
2025· article· en· eLife· Agricultural and Biological Sciences
machine prediction:candidate · noneconsensus · none
4
citations
affunlabeled
The cost of communication in the brain
Brian A. MacVicar, Leigh E. Wicki‐Stordeur, Louis‐Philippe Bernier
2017· letter· en· eLife· Neuroscience
machine prediction:candidate · noneconsensus · none
4
citations
affunlabeled
The impact of light during the night
Tsz Chui Sophia Leung, R. Anne McKinney, Alanna J. Watt
2019· article· en· eLife· Neuroscience
machine prediction:candidate · noneconsensus · none
3
citations
affunlabeled
Finding a worm's internal compass
Catharine H. Rankin, Conny H. Lin
2015· letter· en· eLife· Medicine
machine prediction:candidate · noneconsensus · none
3
citations
affunlabeled
Reality check for transposon enhancers
Julie Brind’Amour, Dixie L. Mager
2019· article· en· eLife· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
3
citations
affunlabeled
Plasmid-powered evolutionary transitions
Ryan A. Melnyk, Cara H. Haney
2017· letter· en· eLife· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
3
citations
affunlabeled
Of starch and spit
Mareike C. Janiak
2019· letter· en· eLife· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
3
citations
affunlabeled
Muscling in on the third dimension
Mohsen Afshar Bakooshli, Penney M. Gilbert
2015· letter· en· eLife· Engineering
machine prediction:candidate · noneconsensus · none
3
citations

How this was built: Screen · Findings · About