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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
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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 69 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
#FAIL: Defining, Understanding and Owning our Failures
Sophia Ikura, Camille Orridge, Teresa Petch, Timothy O’Leary
2015· letter· en· A Nudge Too Far? A Nudge at All? On Paying People to Be Healthy· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
affvenueaboutunlabeled
Medicare Makeover and More
Jane Philpott, Duncan Sinclair
2025· article· en· A Nudge Too Far? A Nudge at All? On Paying People to Be Healthy· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
affaboutunlabeled
Paid Parental Leave: Leaner Might Be Better
Catherine Haeck, Samuel Paré, Pierre Lefèbvre, Philip Merrigan
2019· preprint· en· Project Muse (Johns Hopkins University)· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
The Economics of Healthcare: Challenges and Reform
Mohamed Aslam Sheikh, Asma Mohammed Aslam Sheikh
2024· article· en· Shanlax International Journal of Economics· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Changing Health Care Fields: When, Who, and How
Jo-Louise Huq, Jaana Woiceshyn
2017· article· en· Academy of Management Proceedings· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Canadian Healthcare
Elena Vladimirovna Frolova
2020· article· en· Spravočnik vrača obŝej praktiki (Journal of Family Medicine)· Economics, Econometrics and Finance
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affno abstractunlabeled
It Is Time to Transform Our Health Care System
Jeffrey Turnbull
2011· editorial· en· Journal of Cutaneous Medicine and Surgery· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
afffundaboutunlabeled
Determinants of Physicians' Decisions to Specialize
Robert M. Gagné, Pierre Thomas Léger
2003· preprint· en· RePEc: Research Papers in Economics· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
venueaboutno affunlabeled
Supply Side Economics – the Canadian Way
John Robert Taylor
2011· article· en· Canadian Journal of Plastic Surgery· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations

How this was built: Screen · Findings · About