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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.

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Gut microbiota and health
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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.

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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 ·
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20002025
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Machine labels · sparse coverage
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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 10 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.

affno abstractunlabeled
Challenges of metabolomics in human gut microbiota research
Kirill S. Smirnov, Tanja Maier, Alesia Walker, Silke S. Heinzmann, Sara Forcisi, Inés Martínez +2 more
2016· review· en· International Journal of Medical Microbiology· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
154
citations
afffundno abstractunlabeled
Cooking shapes the structure and function of the gut microbiome
Rachel N. Carmody, Jordan E. Bisanz, Benjamin P. Bowen, Corinne F. Maurice, Svetlana Lyalina, Katherine Louie +11 more
2019· article· en· Nature Microbiology· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
152
citations
affno abstractunlabeled
The microbiome and cancer for clinicians
Sarah Picardo, Bryan Coburn, Aaron R. Hansen
2019· review· en· Critical Reviews in Oncology/Hematology· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
152
citations
afffundno abstractunlabeled
The multiple sclerosis gut microbiota: A systematic review
Ali Mirza, Jessica D. Forbes, Feng Zhu, Çharles N. Bernstein, Gary Van Domselaar, Morag Graham +2 more
2019· review· en· Multiple Sclerosis and Related Disorders· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · metaepi_broadconsensus · none
152
citations
afffundunlabeled
How the microbiome challenges our concept of self
Tobias Rees, Thomas C. G. Bosch, Angela E. Douglas
2018· article· en· PLoS Biology· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
152
citations
afffundunlabeled
Microbiota and Neurological Disorders: A Gut Feeling
Walter H. Moos, Douglas V. Faller, David N. Harpp, Iphigenia Kanara, Julie Pernokas, Whitney R. Powers +1 more
2016· review· en· BioResearch open access· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
148
citations

How this was built: Screen · Findings · About