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
Topic
Pluripotent Stem Cells Research
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.

1,834 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.
1,834 works in the cohort · of 4,299,418page 29 of 37

Labels cover 2 of 1,834 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 1,834 of 1,834 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
Live Imaging of the Developing Mouse Mesonephros
David Grote, Michael Marcotte, Maxime Bouchard
2012· article· en· Methods in molecular biology· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
1
citations
affunlabeled
Towards Early Prediction of Human iPSC Reprogramming Success
Abhineet Singh, Ila Tewari Jasra, Omar Mouhammed, Nidheesh Dadheech, Nilanjan Ray, A. M. James Shapiro
2023· article· en· The Journal of Machine Learning for Biomedical Imaging· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
1
citations
affno abstractunlabeled
ALPHASPERM-INDUCED EPIGENETIC REPROGRAMMING IN SPERM
S. Parks, R.H. Miller, Kristin Brogaard, Paul J. Turek, Timothy G. Jenkins
2024· article· en· Fertility and Sterility· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
1
citations
affno abstractunlabeled
Embryonic Stem Cell Models of Human Brain Tumors
Ludivine Coudière Morrison, Nazanin Tatari, Tamra E. Werbowetski‐Ogilvie
2018· article· en· Methods in molecular biology· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
1
citations
aboutno affunlabeled
Stem cells: A dramatic new therapeutic tool*
Rudi Schmid
2002· review· en· Journal of Gastroenterology and Hepatology· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
1
citations
aboutno affunlabeled
Latimer House
2002· other· en· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations

How this was built: Screen · Findings · About