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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.

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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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Zoonotic diseases and public 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.

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.

1,341 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.
1,341 works in the cohort · of 4,299,418page 18 of 27

Labels cover 6 of 1,341 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 1,341 of 1,341 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
SARS, Pandemics and Public Health
Julia Skelding, Ross Upshur
2010· article· en· Integrated Assessment· Medicine
machine prediction:candidate · noneconsensus · none
1
citations
affunlabeled
Ecosystem Sustainability and Health
David Waltner‐Toews
2004· book· en· Cambridge University Press eBooks· Medicine
machine prediction:candidate · noneconsensus · none
1
citations
affno abstractunlabeled
Human-Animal Health Interactions
Michael Day
2016· article· en· American family physician· Medicine
machine prediction:candidate · noneconsensus · none
1
citations
affno abstractunlabeled
Disease mortality in epidemic models
Fred Brauer
2003· article· en· Dynamics of Continuous Discrete and Impulsive Systems-series B-applications & Algorithms· Medicine
machine prediction:candidate · noneconsensus · none
1
citations
fundno affunlabeled
Occupational Infections
T.C. Aw, K. Gardiner BSc, B. J. Harrington, RGN S. Whitaker, C.A. Jackson, DLO S.M. Ahmed MRCS +1 more
2007· other· en· Medicine
machine prediction:candidate · insufficient_payloadconsensus · none
1
citations
affno abstractunlabeled
Immunology Gone Wild
Vanessa Schipani
2016· article· en· BioScience· Medicine
machine prediction:candidate · noneconsensus · none
1
citations
venueno affunlabeled
From working with animals to humans
Supriya Hota
2020· article· en· Health Science Inquiry· Medicine
machine prediction:candidate · noneconsensus · none
1
citations
venueno affno abstractunlabeled
Letter to the Editor: One Health Initiative
Marguerite Pappaioanou, Harrison C. Spencer
2008· letter· en· Journal of Veterinary Medical Education· Medicine
machine prediction:candidate · noneconsensus · none
1
citations
affno abstractunlabeled
Hypermobile human predators
Chris T. Darimont, Heather M. Bryan
2020· letter· en· Nature Human Behaviour· Medicine
machine prediction:candidate · noneconsensus · none
1
citations
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