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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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Healthcare Operations and Scheduling Optimization
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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.

988 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.
988 works in the cohort · of 4,299,418page 8 of 20

Labels cover 1 of 988 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 988 of 988 works in this cohort. Predictions are machine_predicted_unvalidated teacher distillation outputs. Candidate is the union; consensus is the intersection.

affaboutunlabeled
Substrate for Healthcare Reform
Fredrick K. Orkin, Peter G. Duncan
2009· letter· en· Anesthesiology· Health Professions
distilled prediction:candidate · metaepi_narrow+research_integrityconsensus · research_integrity
11
citations
affno abstractunlabeled
Resource Absorption in a Health Service System
Leonard C. MacLean, Alex Richman
2001· article· en· Health Care Management Science· Health Professions
distilled prediction:candidate · stsconsensus · none
10
citations
affno abstractunlabeled
Operations Research for Occupancy Modeling at Hospital Wards and Its Integration into Practice
N.M. van de Vrugt, A. J. Schneider, Maartje E. Zonderland, David A. Stanford, Richard J. Boucherie
2017· book-chapter· en· International series in management science/operations research/International series in operations research & management science· Health Professions
distilled prediction:candidate · metaresearch+metaepi_narrow+bibliometrics+sts+scholarly_communication+open_science+research_integrity+insufficient_payloadconsensus · metaresearch+sts+scholarly_communication
10
citations
afffundvenueaboutunlabeled
Are there better ways to determine wait times?
Joseph Schaafsma
2006· article· en· Canadian Medical Association Journal· Health Professions
distilled prediction:candidate · sts+insufficient_payloadconsensus · insufficient_payload
10
citations
affunlabeled
Five decades of healthcare simulation
Sally Brailsford, Michael Carter, Sheldon H. Jacobson
2017· article· en· Winter Simulation Conference· Health Professions
distilled prediction:candidate · stsconsensus · none
9
citations
affvenueno abstractunlabeled
Changes in waiting lists over time
Lorne Bellan
2008· article· en· Canadian Journal of Ophthalmology· Health Professions
distilled prediction:candidate · insufficient_payloadconsensus · none
9
citations

How this was built: Screen · Findings · About