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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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Medical Coding and Health Information
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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
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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.

679 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.
679 works in the cohort · of 4,299,418page 6 of 14

Labels cover 6 of 679 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 679 of 679 works in this cohort. Predictions are machine_predicted_unvalidated teacher distillation outputs. Candidate is the union; consensus is the intersection.

venueno affunlabeled
It’s hard to ignore the data when the data is in the room
Margaret Ann Bolick, Leilani Pai, Rachel Funk, Matthew Voigt
2025· article· en· International Journal for Students as Partners· Health Professions
distilled prediction:candidate · sts+open_scienceconsensus · none
3
citations
venueno affunlabeled
Improvements in Neoplasm Classification in the International Classification of Diseases, Eleventh Revision: Systematic Comparative Study With the Chinese Clinical Modification of the International Classification of Diseases, Tenth Revision
Yicong Xu, Jingya Zhou, Hongxia Li, Dong Cai, Huanbing Zhu, Shengdong Pan
2024· article· en· Interactive Journal of Medical Research· Health Professions
distilled prediction:candidate · metaresearch+research_integrityconsensus · none
3
citations
affunlabeled
Coder Educator: The Way Forward
Ellen Logan, María de Mater O'Neill, Corrie Martin
2003· article· en· Health Information Management· Health Professions
distilled prediction:candidate · sts+insufficient_payloadconsensus · insufficient_payload
2
citations
affunlabeled
Transition to the ICD-10
Christina Wolleon
2015· article· en· Professional Case Management· Health Professions
distilled prediction:candidate · insufficient_payloadconsensus · insufficient_payload
2
citations
affno abstractunlabeled
Up from ‘Clinical Epidemiology’ & EBM
Olli S. Miettinen
2010· book-chapter· en· Health Professions
distilled prediction:candidate · metaepi_narrow+research_integrity+insufficient_payloadconsensus · research_integrity+insufficient_payload
2
citations
affaboutunlabeled
Linking health databases for research.
Richard Birtwhistle, Marshall Godwin, Jannet Ann Leggett, Ken Martin
2015· article· fr· PubMed· Health Professions
distilled prediction:candidate · metaresearch+stsconsensus · metaresearch
2
citations
affunlabeled
Administrative Databases
Leslíe L. Roos, Patrick S. Romano, Patricia Fergusson
2014· other· en· Wiley StatsRef: Statistics Reference Online· Health Professions
distilled prediction:candidate · metaepi_narrow+insufficient_payloadconsensus · insufficient_payload
2
citations
affunlabeled
Coding of Thoughts, Words and Things
Madonna Kemp, Sue Walker, P. R. SCOTT
2005· article· en· Health Information Management· Health Professions
distilled prediction:candidate · noneconsensus · none
2
citations
venueno affunlabeled
Global Trends of Medical Misadventures Using International Classification of Diseases, Tenth Revision Cluster Y62-Y69 Comparing Pre–, Intra–, and Post–COVID-19 Pandemic Phases: Protocol for a Retrospective Analysis Using the TriNetX Platform
Rosario Caruso, Marco Di Muzio, Emanuele Di Simone, Sara Dionisi, Arianna Magon, Gianluca Conte +5 more
2024· article· en· JMIR Research Protocols· Health Professions
distilled prediction:candidate · noneconsensus · none
2
citations
venueno affunlabeled
10.1016/s1069-5648(14)60032-0
Cindy Hughes
2000· article· en· Time to knit· Health Professions
distilled prediction:candidate · insufficient_payloadconsensus · insufficient_payload
2
citations
aboutno affunlabeled
Using ICD-10 to optimize patient care
Pam Jodock
2015· article· en· Nursing Management· Health Professions
distilled prediction:candidate · insufficient_payloadconsensus · none
1
citations

How this was built: Screen · Findings · About