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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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SARS-CoV-2 detection and testing
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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
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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.

1,161 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.
1,161 works in the cohort · of 4,299,418page 4 of 24

Labels cover 2 of 1,161 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 1,161 of 1,161 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.

afffundunlabeled
One-Year Update on Salivary Diagnostic of COVID-19
Douglas Carvalho Caixeta, Stephanie Wutke Oliveira, Léia Cardoso-Sousa, Thúlio Marquez Cunha, Luíz Ricardo Goulart, Mário Machado Martins +4 more
2021· review· en· Frontiers in Public Health· Medicine
machine prediction:candidate · noneconsensus · none
32
citations
affno abstractunlabeled
Group Testing and Batch Verification
Gregory M. Zaverucha, Douglas R. Stinson
2010· book-chapter· en· Lecture notes in computer science· Medicine
machine prediction:candidate · noneconsensus · none
32
citations
aboutno affunlabeled
Use of Wastewater Metrics to Track COVID-19 in the US
Meri R.J. Varkila, Maria E. Montez‐Rath, Joshua A. Salomon, Xue Yu, Geoffrey A. Block, Douglas K Owens +3 more
2023· article· en· JAMA Network Open· Medicine
machine prediction:candidate · noneconsensus · none
31
citations
afffundgemma · no categorygpt · no categorymodels agree
SARS-CoV-2 On-the-Spot Virus Detection Directly from Patients
Nadav Ben-Assa, Rawi Naddaf, Tal Gefen, Tal Capucha, Haitham Hajjo, Noa Mandelbaum +9 more
2020· preprint· en· medRxiv· Medicine
machine prediction:candidate · noneconsensus · none
31
citations
affunlabeled
Survival of SARS-CoV-2 in wastewater
Samendra P. Sherchan, Ocean Thakali, Luisa A. Ikner, Charles P. Gerba
2023· article· en· The Science of The Total Environment· Medicine
machine prediction:candidate · noneconsensus · none
30
citations
affno abstractunlabeled
Laboratory detection methods for the human coronaviruses
Ehsan Shabani, Sayeh Dowlatshahi, Mohammad J. Abdekhodaie
2020· review· en· European Journal of Clinical Microbiology & Infectious Diseases· Medicine
machine prediction:candidate · noneconsensus · none
30
citations

How this was built: Screen · Findings · About