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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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Heparin-Induced Thrombocytopenia and Thrombosis
Retraction
Abstract
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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.

770 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.
770 works in the cohort · of 4,299,418page 2 of 16

Labels cover 1 of 770 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 770 of 770 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
How I Diagnose and Manage HIT
Theodore E. Warkentin
2011· review· en· Hematology· Medicine
machine prediction:candidate · noneconsensus · none
157
citations
afffundunlabeled
Bivalirudin
Andreas Greinacher, Andreas Koster, Theodore E. Warkentin
2008· review· en· Thrombosis and Haemostasis· Medicine
machine prediction:candidate · noneconsensus · none
154
citations
affno abstractunlabeled
Direct thrombin inhibitors
Jeffrey I. Weitz, Mark Crowther
2002· review· en· Thrombosis Research· Medicine
machine prediction:candidate · noneconsensus · none
131
citations
affunlabeled
Soluble Urokinase Receptor (SuPAR) in COVID-19–Related AKI
Tariq U. Azam, Husam Shadid, Pennelope Blakely, Patrick O’Hayer, Hanna Berlin, Michael Pan +21 more
2020· article· en· Journal of the American Society of Nephrology· Medicine
machine prediction:candidate · noneconsensus · none
129
citations
affno abstractunlabeled
Heparin-Induced Thrombocytopenia
Theodore E. Warkentin
2007· review· en· Hematology/Oncology Clinics of North America· Medicine
machine prediction:candidate · noneconsensus · none
123
citations
affno abstractunlabeled
HIT paradigms and paradoxes
Theodore E. Warkentin
2011· review· en· Journal of Thrombosis and Haemostasis· Medicine
machine prediction:candidate · noneconsensus · none
106
citations
affno abstractunlabeled
Vaccine-induced immune thrombotic thrombocytopenia
2022· review· en· White Rose Research Online (University of Leeds, The University of Sheffield, University of York)· Medicine
machine prediction:candidate · noneconsensus · none
99
citations
affunlabeled
Heparin-induced Thrombocytopenia
John G. Kelton
2009· review· en· Haemostasis· Medicine
machine prediction:candidate · noneconsensus · none
98
citations
venueno affunlabeled
Incidence and causes of heparin-induced skin lesions
Marc Schindewolf, Sandra L. Schwaner, Manfred Wolter, H. Kroll, Andreas Recke, R. Kaufmann +3 more
2009· article· en· Canadian Medical Association Journal· Medicine
machine prediction:candidate · noneconsensus · none
94
citations
affunlabeled
Think of HIT
Theodore E. Warkentin
2006· review· en· Hematology· Medicine
machine prediction:candidate · noneconsensus · none
92
citations

How this was built: Screen · Findings · About