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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 and healthcare impacts
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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.

2,192 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.
2,192 works in the cohort · of 4,299,418page 2 of 44

Labels cover 8 of 2,192 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 2,192 of 2,192 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
The Risk and Prognosis of COVID-19 Infection in Cancer Patients
Ghada Elgohary, Shahrukh K. Hashmi, Jan Styczyński, Mohamed A. Kharfan‐Dabaja, Rehab M. Alblooshi, Rafael de la Cámara +11 more
2020· review· en· Hematology/Oncology and Stem Cell Therapy· Medicine
machine prediction:candidate · noneconsensus · none
152
citations
affunlabeled
Global impact of COVID-19 on stroke care
Raul G. Nogueira, Mohamad Abdalkader, Muhammed M. Qureshi, Michael Frankel, Malek Mansour, Hiroshi Yamagami +265 more
2021· article· en· International Journal of Stroke· Medicine
machine prediction:candidate · noneconsensus · none
150
citations
afffundvenueaboutunlabeled
Injuries in the time of COVID-19
Glenn Keays, Debbie Freeman, Isabelle Gagnon
2020· article· en· Health Promotion and Chronic Disease Prevention in Canada· Medicine
machine prediction:candidate · noneconsensus · none
123
citations
affaboutunlabeled
Sacrificed: Ontario Healthcare Workers in the Time of COVID-19
James T. Brophy, Margaret M. Keith, Michael Hurley, Jane McArthur
2020· article· en· NEW SOLUTIONS A Journal of Environmental and Occupational Health Policy· Medicine
machine prediction:candidate · noneconsensus · none
118
citations
affunlabeled
Considerations for cardiac catheterization laboratory procedures during the <scp>COVID</scp>‐19 pandemic perspectives from the Society for Cardiovascular Angiography and Interventions Emerging Leader Mentorship (<scp><i>SCAI ELM</i></scp>) Members and Graduates
Molly Szerlip, Saif Anwaruddin, Herbert D. Aronow, Mauricio G. Cohen, Matthew J. Daniels, Payam Dehghani +19 more
2020· review· en· Catheterization and Cardiovascular Interventions· Medicine
machine prediction:candidate · noneconsensus · none
108
citations
fundno affno abstractunlabeled
Crowdsourcing a crisis response for COVID-19 in oncology
Aakash Desai, Jeremy L. Warner, Nicole M. Kuderer, Mike Thompson, Corrie Painter, Gary H. Lyman +1 more
2020· article· en· Nature Cancer· Medicine
machine prediction:candidate · noneconsensus · none
82
citations

How this was built: Screen · Findings · About