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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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Spatial and Spatio-temporal Epidemiology
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Retraction
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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.

72 results · 1 filter active ·
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20102025
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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.
72 works in the cohort · of 4,299,418page 1 of 2

Labels cover 1 of 72 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 72 of 72 works in this cohort. Predictions are machine_predicted_unvalidated teacher distillation outputs. Candidate is the union; consensus is the intersection.

affno abstractunlabeled
Review of methods for space–time disease surveillance
Colin Robertson, Trisalyn Nelson, Ying C. MacNab, Andrew Lawson
2010· review· en· Spatial and Spatio-temporal Epidemiology· Medicine
distilled prediction:candidate · metaresearch+metaepi_narrowconsensus · none
152
citations
afffundno abstractunlabeled
Supervised learning and prediction of spatial epidemics
Gyanendra Pokharel, Rob Deardon
2014· article· en· Spatial and Spatio-temporal Epidemiology· Agricultural and Biological Sciences
distilled prediction:candidate · noneconsensus · none
15
citations
aboutno affunlabeled
Predicting the odds of chronic wasting disease with Habitat Risk software
W. David Walter, Brenda J. Hanley, Cara E. Them, Corey I. Mitchell, James F. Kelly, Daniel Grove +3 more
2024· article· en· Spatial and Spatio-temporal Epidemiology· Biochemistry, Genetics and Molecular Biology
distilled prediction:candidate · noneconsensus · none
5
citations

How this was built: Screen · Findings · About