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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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Acute Ischemic Stroke Management
Retraction
Abstract
Evidence source
Study design
Label agreement
Label status

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.

6,330 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.
6,330 works in the cohort · of 4,299,418page 26 of 127

Labels cover 16 of 6,330 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 6,330 of 6,330 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
International Experience in Stroke Registries
Frank L. Silver, Moira K. Kapral, M. Patrice Lindsay, Jack V. Tu, Janice A. Richards
2006· article· en· American Journal of Preventive Medicine· Medicine
machine prediction:candidate · noneconsensus · none
33
citations
afffundunlabeled
Stroke: Working toward a Prioritized World Agenda
Vladimir Hachinski, Geoffrey A. Donnan, Philip B. Gorelick, Werner Hacke, Steven C. Cramer, Markku Kaste +47 more
2010· article· en· Cerebrovascular Diseases· Medicine
machine prediction:candidate · noneconsensus · none
33
citations
aboutno affunlabeled
Endovascular Thrombectomy for Large Ischemic Core Stroke
Chang Liu, Mohamad Abdalkader, Hongfei Sang, Amrou Sarraj, Bruce Campbell, Zhongrong Miao +25 more
2025· review· en· Neurology· Medicine
machine prediction:candidate · noneconsensus · none
33
citations
affno abstractunlabeled
Current treatment for childhood arterial ischaemic stroke
Peter B. Sporns, Heather J. Fullerton, Sarah Lee, Adam Kirton, Moritz Wildgruber
2021· review· en· The Lancet Child & Adolescent Health· Medicine
machine prediction:candidate · noneconsensus · none
33
citations
aboutno affunlabeled
Interaction between time, ASPECTS, and clinical mismatch
Shashvat M. Desai, Daniel A. Tonetti, Bradley J. Molyneaux, Kunakorn Atchaneeyasakul, Marcelo Rocha, Tudor G. Jovin +1 more
2020· article· en· Journal of NeuroInterventional Surgery· Medicine
machine prediction:candidate · noneconsensus · none
32
citations
affunlabeled
Venous imaging-based biomarkers in acute ischaemic stroke
Josep Munuera, Gerard Blasco, María Hernández‐Pérez, Pepus Daunis‐i‐Estadella, Antoni Dávalos, David S. Liebeskind +7 more
2016· review· en· Journal of Neurology Neurosurgery & Psychiatry· Medicine
machine prediction:candidate · noneconsensus · none
32
citations
affunlabeled
Massive Cerebral Infarction
Suresh Subramaniam, Michael D. Hill
2005· review· en· The Neurologist· Medicine
machine prediction:candidate · noneconsensus · none
32
citations

How this was built: Screen · Findings · About