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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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Health Systems, Economic Evaluations, Quality of Life
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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.

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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.

6,862 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.
6,862 works in the cohort · of 4,299,418page 75 of 138

Labels cover 97 of 6,862 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 6,862 of 6,862 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.

aboutno affunlabeled
International experience in determining the cost-effectiveness thresholds
T. P. Bezdenezhnykh, Н. З. Мусина, V. K. Fedyaeva, T. S. Tepcova, В. А. Лемешко, V. V. Omelyanovsky
2019· article· en· FARMAKOEKONOMIKA Modern Pharmacoeconomics and Pharmacoepidemiology· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
2
citations
affvenueaboutunlabeled
Medicare’s Evolution: National Pharmacare and Shared Leadership
Joanna Nemis‐White, Emily Torr, John Aylen, Amédé Gogovor, Lesli Martin, Jonathan Mitchell +2 more
2019· article· en· Healthcare Quarterly· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
2
citations
afffundunlabeled
Risk Management During the Transition From Hospital to Home: A Multiple Case Study Documenting the Experience of Patients Living With a Major Neurocognitive Disorder, Their Caregivers, and Healthcare Professionals
Véronique Provencher, Chantal Viscogliosi, Julie Lacerte, Monia D’Amours, Didier Mailhot‐Bisson, Lise Gagnon +1 more
2024· article· en· Journal of Patient Experience· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
2
citations
aboutno affunlabeled
Analysis Of Articles on Evidence-Based Medicine
Umut Beylik
2021· article· en· Gevher Nesibe Journal IESDR· Economics, Econometrics and Finance
machine prediction:candidate · metaresearch+bibliometricsconsensus · none
2
citations
affvenueunlabeled
Troutville: Where People Discuss Fairness Issues
Yukiko Asada, Robin Urquhart, Marion Brown, Grace Warner, Mary McNally, Andrea Murphy
2020· article· en· Canadian Journal of Bioethics· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
2
citations
affunlabeled
Value of Research on Safety Effects of Actions
Ezra Hauer, James A. Bonneson, Raghavan Srinivasan, Geni Bahar
2012· article· en· Transportation Research Record Journal of the Transportation Research Board· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
2
citations
affunlabeled
Understanding Measures of Association
Suneel Upadhye, Mohammad Alavinia, Dinesh Kumbhare
2019· article· en· American Journal of Physical Medicine & Rehabilitation· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
2
citations

How this was built: Screen · Findings · About