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
Gut microbiota and health
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.

4,457 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.
4,457 works in the cohort · of 4,299,418page 27 of 90

Labels cover 7 of 4,457 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 4,457 of 4,457 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
Independent and Interactive Effects of Habitually Ingesting Fermented Milk Products Containing Lactobacillus casei Strain Shirota and of Engaging in Moderate Habitual Daily Physical Activity on the Intestinal Health of Older People
Yukitoshi Aoyagi, Ryuta Amamoto, Sung Jin Park, Yusuke Honda, Kazuhito Shimamoto, Akira Kushiro +6 more
2019· article· en· Frontiers in Microbiology· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
42
citations
affno abstractunlabeled
Gut Microbiome and Behavior
Jane A. Foster
2016· review· en· International review of neurobiology· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
41
citations
afffundunlabeled
Human Catestatin Alters Gut Microbiota Composition in Mice
Mohammad Fazle Rabbi, Peris M. Munyaka, Nour Eissa, Marie‐Hélène Metz‐Boutigue, Ehsan Khafipour, Jean‐Eric Ghia
2017· article· en· Frontiers in Microbiology· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
41
citations
affunlabeled
Gut microbiome is associated with multiple sclerosis activity in children
Mary Horton, Kathryn McCauley, Douglas Fadrosh, Kei E. Fujimura, Jennifer Graves, Jayne Ness +20 more
2021· article· en· Annals of Clinical and Translational Neurology· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
41
citations
afffundno abstractunlabeled
Zebrafish: a big fish in the study of the gut microbiota
Jeffrey K. Cornuault, Gabriel Byatt, Marie-Ève Paquet, Paul De Koninck, Sylvain Moineau
2021· review· en· Current Opinion in Biotechnology· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
40
citations

How this was built: Screen · Findings · About