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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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The Lancet Oncology
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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
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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.

832 results · 1 filter active ·
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20002025
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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.
832 works in the cohort · of 4,299,418page 12 of 17

Labels cover 9 of 832 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 832 of 832 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
A brave new framework for glioma drug development
Kelly Hotchkiss, Philipp Karschnia, Karisa C. Schreck, Marjolein Geurts, Timothy F. Cloughesy, Jason T. Huse +33 more
2024· review· en· The Lancet Oncology· Medicine
machine prediction:candidate · noneconsensus · none
25
citations
affno abstractunlabeled
Global cancer research in the post-pandemic world
Deborah Mukherji, Raúl Murillo, Mieke Van Hemelrijck, Verna Vanderpuye, Omar Shamieh, Julie Torode +5 more
2021· article· en· The Lancet Oncology· Medicine
machine prediction:candidate · noneconsensus · none
23
citations
afffundno abstractunlabeled
The human crisis in cancer: a Lancet Oncology Commission
Gary Rodin, Dario Trapani, Mac Skelton, Karla Unger‐Saldaña, Beverley M. Essue, Rille Pihlak +29 more
2025· review· en· The Lancet Oncology· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
23
citations
affno abstractunlabeled
Surgery versus SABR for NSCLC
Alexander V. Louie, David A. Palma
2013· letter· en· The Lancet Oncology· Medicine
machine prediction:candidate · noneconsensus · none
22
citations
affno abstractunlabeled
A roadmap for restoring trust in Big Data
Mark Lawler, Andrew D. Morris, Richard Sullivan, Ewan Birney, Anna Middleton, Lydia Makaroff +3 more
2018· article· en· The Lancet Oncology· Medicine
machine prediction:candidate · noneconsensus · none
21
citations
afffundno abstractunlabeled
New approaches to cancer care in a COVID-19 world
John Butler, Christian Finley, Charles Norell, Samantha Harrison, Heather Bryant, Michael Patrick Achiam +26 more
2020· letter· en· The Lancet Oncology· Medicine
machine prediction:candidate · noneconsensus · none
21
citations
affaboutno abstractunlabeled
Access to radiotherapy among circumpolar Inuit populations
Jessica Chan, Jeppe Friborg, Mikhail Chernov, Mikhail Cherkashin, Cai Grau, Michael Brundage +1 more
2019· review· en· The Lancet Oncology· Medicine
machine prediction:candidate · noneconsensus · none
15
citations

How this was built: Screen · Findings · About