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
SARS-CoV-2 and COVID-19 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.

4,166 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.
4,166 works in the cohort · of 4,299,418page 10 of 84

Labels cover 17 of 4,166 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 4,166 of 4,166 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
SARS-CoV-2 Variants and Clinical Outcomes: A Systematic Review
Indira R. Mendiola‐Pastrana, Eduardo López‐Ortiz, José G. Río de la Loza-Zamora, James González, Anel Gómez‐García, Geovani López-Ortiz
2022· review· en· Life· Medicine
machine prediction:candidate · noneconsensus · none
70
citations
affno abstractunlabeled
Interferon beta-1b for COVID-19
Sarah Shalhoub
2020· letter· en· The Lancet· Medicine
machine prediction:candidate · noneconsensus · none
70
citations
afffundunlabeled
A proteome-scale map of the SARS-CoV-2–human contactome
Dae‐Kyum Kim, Benjamin Weller, Chung‐Wen Lin, Dayag Sheykhkarimli, Jennifer J. Knapp, Guillaume Dugied +46 more
2022· article· en· Nature Biotechnology· Medicine
machine prediction:candidate · noneconsensus · none
68
citations
affunlabeled
Novel genes and sex differences in COVID-19 severity
Raquel Cruz, Silvia Diz‐de Almeida, Miguel López de Heredia, Inés Quintela, Francisco C. Ceballos, Guillermo Pita +159 more
2022· review· en· Human Molecular Genetics· Medicine
machine prediction:candidate · noneconsensus · none
66
citations
afffundunlabeled
SARS-CoV-2 Omicron spike mediated immune escape and tropism shift
Bo Meng, Isabella A.T.M. Ferreira, Adam Abdullahi, Niluka Goonawardane, Akatsuki Saito, Izumi Kimura +46 more
2021· preprint· en· bioRxiv (Cold Spring Harbor Laboratory)· Medicine
machine prediction:candidate · noneconsensus · none
64
citations

How this was built: Screen · Findings · About