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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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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 15 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.

fundno affunlabeled
One health governance: recent advances in Brazil
Mayumi Duarte Wakimoto, Rodrigo Caldas Menezes, Tiago Nery, Sandro Antônio Pereira, Valdiléa G. Veloso
2025· article· en· One Health· Medicine
machine prediction:candidate · noneconsensus · none
2
citations
affaboutunlabeled
Enabling academic One Health environments.
Bonnie Buntain, Lisa Allen Scott, Michelle North, Melanie Rock, J. Hatfield
2015· book-chapter· en· CABI eBooks· Medicine
machine prediction:candidate · noneconsensus · none
2
citations
affunlabeled
Approaches and methods to study wildlife cancer
Mathieu Giraudeau, Orsolya Vincze, Sophie M. Dupont, Tuul Sepp, Ciara Baines, Jean‐François Lemaître +24 more
2024· review· en· Journal of Animal Ecology· Medicine
machine prediction:candidate · noneconsensus · none
2
citations
affno abstractunlabeled
One Health - an ambiguous concept under debate
Maria Lúcia Frizon Rizzotto, Ana Maria Costa, Alexandre Pessoa Dias, Heleno Rodrigues Corrêa Filho, Karen Friedrich, Lia Giraldo da Silva Augusto
2024· article· en· Saúde em Debate· Medicine
machine prediction:candidate · noneconsensus · none
2
citations
affvenueaboutunlabeled
Zoonotic infections of the Canadian Arctic
James E. Burns, Gunjan Mhapankar, Elaine Kilabuk, Justin Penner
2025· review· en· Canadian Medical Association Journal· Medicine
machine prediction:candidate · noneconsensus · none
2
citations
affvenueunlabeled
Spatial data issues in geographical zoonoses research
Colin Robertson, Lauren Yee, J Metelka, Craig Stephen
2016· article· en· Canadian Geographies / Géographies canadiennes· Medicine
machine prediction:candidate · noneconsensus · none
2
citations
affunlabeled
An ecological and conservation perspective.
C. LeAnn White, Julia S. Lankton, Daniel P. Walsh, Jonathan M. Sleeman, Craig Stephen
2020· book-chapter· en· CABI eBooks· Medicine
machine prediction:candidate · noneconsensus · none
2
citations

How this was built: Screen · Findings · About