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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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Journal of Clinical 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
fundfunder
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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.

9,514 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.
9,514 works in the cohort · of 4,299,418page 107 of 191

Labels cover 106 of 9,514 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 9,514 of 9,514 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.

aboutno affunlabeled
The utilization of new oncology drugs: A global perspective
Bertil Jönsson, Franz von Lichtenberg, Jonas Lundkvist, Cecilia Svedman, N. Wilking
2007· article· en· Journal of Clinical Oncology· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
1
citations
affaboutunlabeled
The experience of a sample of Canadian men with breast cancer
Edith Pituskin, Beverly Williams, Kristine Martin‐McDonald, H. Au
2006· article· en· Journal of Clinical Oncology· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
1
citations
affunlabeled
The effect of a cancer diagnosis on disability status
Elizabeth B. Habermann, Beth A Virnig, Patricia M. McGovern, A. Marshall McBean, Bruce H. Alexander, Nancy N. Baxter
2009· article· en· Journal of Clinical Oncology· Medicine
machine prediction:candidate · noneconsensus · none
1
citations
affno abstractunlabeled
Witness
Daniel Rayson
2005· article· en· Journal of Clinical Oncology
machine prediction:candidate · insufficient_payloadconsensus · none
1
citations
affaboutunlabeled
AI in oncology: Resident perspectives by gender and tech literacy.
Fernanda Malucelli Favorito, Laura Collie, Thomas Kennedy, Jacqueline Justino Nabhen, Amir H. Safavi, Giovanni Guido Cerri +1 more
2024· article· en· Journal of Clinical Oncology· Medicine
machine prediction:candidate · noneconsensus · none
1
citations

How this was built: Screen · Findings · About