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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 Clinical Research Studies
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
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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.

2,625 results · 1 filter active ·
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20002025
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Machine labels · sparse coverage
Evidence
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Citations
An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
2,625 works in the cohort · of 4,299,418page 2 of 53

Labels cover 25 of 2,625 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 2,625 of 2,625 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
COVID-19: breaking down a global health crisis
Saad I. Mallah, Omar Ghorab, Sabrina Al-Salmi, Omar S. Abdellatif, Tharmegan Tharmaratnam, Mina Iskandar +5 more
2021· review· en· Annals of Clinical Microbiology and Antimicrobials· Medicine
machine prediction:candidate · noneconsensus · none
375
citations
afffundno abstractunlabeled
Understanding COVID-19-associated coagulopathy
Edward M. Conway, Nigel Mackman, Ronald Q. Warren, Alisa S. Wolberg, Laurent O. Mosnier, Robert A. Campbell +8 more
2022· review· en· Nature reviews. Immunology· Medicine
machine prediction:candidate · noneconsensus · none
359
citations
affno abstractunlabeled
An aberrant STAT pathway is central to COVID-19
T. Matsuyama, Shawn P. Kubli, Steven K. Yoshinaga, Klaus Pfeffer, Tak W. Mak
2020· review· en· Cell Death and Differentiation· Medicine
machine prediction:candidate · noneconsensus · none
308
citations
affunlabeled
A real-time dashboard of clinical trials for COVID-19
Kristian Thorlund, Louis Dron, Jay Park, Grace Hsu, Jamie I. Forrest, Edward J. Mills
2020· letter· en· The Lancet Digital Health· Medicine
machine prediction:candidate · noneconsensus · none
246
citations

How this was built: Screen · Findings · About