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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 Policy and Management
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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.

3,600 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.
3,600 works in the cohort · of 4,299,418page 21 of 72

Labels cover 5 of 3,600 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 3,600 of 3,600 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.

affvenueunlabeled
Evidence for Health: From Patient Choice to Global Policy
Vanessa Kitchin
2014· article· fr· Journal of the Canadian Health Libraries Association / Journal de l Association de bilbiothèques de la santé du Canada· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
7
citations
affaboutunlabeled
Health reform and privatization in Alberta
John Church, Neale Smith
2006· article· fr· Canadian Public Administration· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
7
citations
affaboutunlabeled
Does CEO compensation impact patient satisfaction?
Kunle Akingbola, Herman A. van den Berg
2015· article· en· Journal of Health Organization and Management· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
7
citations
affno abstractunlabeled
Urban mortality and the repeal of federal prohibition
David S. Jacks, Krishna Pendakur, Hitoshi Shigeoka
2023· article· en· Explorations in Economic History· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
7
citations
affunlabeled
How do Hospitals Respond to Payment Incentives?
Gautam Gowrisankaran, Keith A. Joiner, Jianjing Lin
2019· report· en· National Bureau of Economic Research· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
7
citations
affaboutunlabeled
Health Resource Allocation
Tom Noseworthy
2011· article· en· Journal of Legal Medicine· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
7
citations
venueaboutno affunlabeled
Supreme Court slaps for-sale sign on medicare
Lawrie McFarlane
2005· article· en· Canadian Medical Association Journal· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
7
citations
fundno affunlabeled
A Denial a Day Keeps the Doctor Away
Abe Dunn, Joshua D. Gottlieb, Adam Hale Shapiro, Daniel Sonnenstuhl, Pietro Tebaldi
2023· article· en· Federal Reserve Bank of San Francisco, Working Paper Series· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
7
citations
aboutno affunlabeled
CEO Turnover Among U.S. Acute Care Hospitals, 2006–2015
Larry R. Hearld, William Opoku-Agyeman, Dae Hyun Kim, Amy Yarbrough Landry
2019· article· en· Journal of Healthcare Management· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
7
citations

How this was built: Screen · Findings · About