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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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Annals of Internal Medicine
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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.

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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.

865 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.
865 works in the cohort · of 4,299,418page 12 of 18

Labels cover 1 of 865 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 865 of 865 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
Travel-Associated Zika Virus Disease
Davidson H. Hamer, Lin H. Chen, Michael Libman, Martin P. Grobusch, Douglas H. Esposito
2017· letter· en· Annals of Internal Medicine· Medicine
machine prediction:candidate · noneconsensus · none
1
citations
aboutno affunlabeled
Echinacea for the Common Cold
Paul Mittman, Debra A. Wollner, Linda Kim
2003· letter· en· Annals of Internal Medicine· Medicine
machine prediction:candidate · noneconsensus · none
1
citations
affunlabeled
Nephrology: What You May Have Missed in 2024
Abdulla Alfadhel, Razan Alfarsi, Hussa Alkhajah, Ashwini R. Sehgal
2025· review· en· Annals of Internal Medicine· Medicine
machine prediction:candidate · noneconsensus · none
1
citations
affaboutunlabeled
Guidelines to Limit Added Sugar Intake
Melissa Brouwers, Amir Qaseem, Karen Spithoff, Iván D. Flórez
2017· letter· en· Annals of Internal Medicine· Medicine
machine prediction:candidate · noneconsensus · none
1
citations
aboutno affunlabeled
Moving From Idealism to Realism With Data Sharing
Keith Marsolo, Kevin P. Weinfurt, Karen L. Staman, Bradley G. Hammill
2023· editorial· en· Annals of Internal Medicine· Computer Science
machine prediction:candidate · metaresearch+open_scienceconsensus · metaresearch
1
citations
affunlabeled
Endocrinology: What You May Have Missed in 2024
Mohamed Aman, Athavi Jeevananthan, Maria Martinez-Cruz, Neesha Namasingh, Bryan C. Batch
2025· review· en· Annals of Internal Medicine· Medicine
machine prediction:candidate · noneconsensus · none
1
citations
affaboutunlabeled
Albumin Administration in Patients With Sepsis
Bram Rochwerg, Waleed Alhazzani, Roman Jaeschke
2015· letter· en· Annals of Internal Medicine· Medicine
machine prediction:candidate · noneconsensus · none
1
citations

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