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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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npj Digital Medicine
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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.

214 results · 1 filter active ·
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20182025
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Machine labels · sparse coverage
Evidence
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An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
214 works in the cohort · of 4,299,418page 3 of 5

Labels cover 0 of 214 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 214 of 214 works in this cohort. Predictions are machine_predicted_unvalidated teacher distillation outputs. Candidate is the union; consensus is the intersection.

affunlabeled
Channel management in virtual care
Matt Desruisseaux, Vess Stamenova, R. Sacha Bhatia, Onil Bhattacharyya
2020· article· en· npj Digital Medicine· Medicine
distilled prediction:candidate · noneconsensus · none
13
citations
afffundunlabeled
The early warning paradox
Hugh Logan Ellis, Edward Palmer, James Teo, Martin Whyte, Kenneth Rockwood, Zina Ibrahim
2025· article· en· npj Digital Medicine· Computer Science
distilled prediction:candidate · noneconsensus · none
13
citations
affunlabeled
Representational ethical model calibration
Robert Carruthers, Isabel Straw, James K. Ruffle, Daniel M. Herron, Amy Nelson, Danilo Bzdok +3 more
2022· article· en· npj Digital Medicine· Medicine
distilled prediction:candidate · metaresearch+research_integrity+insufficient_payloadconsensus · none
11
citations
affunlabeled
AI and innovation in clinical trials
Aarav Badani, Fábio Ynoe de Moraes, Philipp Kickingereder, Caroline Chung, Alireza Mansouri
2025· article· en· npj Digital Medicine· Medicine
distilled prediction:candidate · metaresearchconsensus · none
11
citations

How this was built: Screen · Findings · About