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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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COVID-19 epidemiological studies
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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.

3,341 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.
3,341 works in the cohort · of 4,299,418page 20 of 67

Labels cover 12 of 3,341 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 3,341 of 3,341 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.

affno abstractunlabeled
Patterns amidst the turmoil: COVID-19 and cities
Shauna Brail
2021· article· en· Environment and Planning B Urban Analytics and City Science· Mathematics
machine prediction:candidate · noneconsensus · none
15
citations
aboutno affunlabeled
Fighting Pandemics: Inspiration from Islam
Hamid Ashraf, Ahmad Faraz, Md. Obayed Raihan, Sanjay Kalra
2020· article· en· Journal of the Pakistan Medical Association· Mathematics
machine prediction:candidate · noneconsensus · none
15
citations
affunlabeled
A mathematical model of COVID-19 transmission
R. Jayatilaka, Rajan Patel, Manika Brar, Yiwen Tang, N. Jisrawi, Farrukh Chishtie +2 more
2021· article· en· Materials Today Proceedings· Mathematics
machine prediction:candidate · noneconsensus · none
15
citations
affunlabeled
What Can We Learn From Others to Develop a Regional Centre for Infectious Diseases in ASEAN? Comment on "Operationalising Regional Cooperation for Infectious Disease Control: A Scoping Review of Regional Disease Control Bodies and Networks"
Yot Teerawattananon, Saudamini Vishwanath Dabak, Wanrudee Isaranuwatchai, Thongchai Lertwilairatanapong, Asrul Akmal Shafie, Auliya A. Suwantika +3 more
2022· review· en· International Journal of Health Policy and Management· Mathematics
machine prediction:candidate · noneconsensus · none
15
citations
aboutno affunlabeled
Severe acute respiratory syndrome (SARS)
M. Woodhead, Santiago Ewig, Andrew S. Torres
2003· editorial· en· European Respiratory Journal· Mathematics
machine prediction:candidate · noneconsensus · none
14
citations
affunlabeled
COVID-19 in Europe: Dataset at a sub-national level
Hichem Omrani, Madalina Modroiu, Javier Lenzi, Bilel Omrani, Zied Said, Marc Suhrcke +3 more
2021· article· en· Data in Brief· Mathematics
machine prediction:candidate · noneconsensus · none
14
citations

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