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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.

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.

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 126 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.

affunlabeled
Urine Biomarkers Predict Treatment Response in the MENTOR Study
Prapa Pattrapornpisut, Sarah Moran, Gary D. Bader, Changjiang Xu, Paul C. Boutros, Fernando C. Fervenza +3 more
2021· article· en· Journal of the American Society of Nephrology· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
affgpt · no categorygrok · no categoryopus · no categorymodels split
Using the Information Metric to Analyze Clinical Rating Scales
J. O. Ramsay, Juan Li, Charles N. Bernstein, Ruth Ann Marrie, Joakim Wallmark, Marie Wiberg
2025· article· en· Journal of Educational and Behavioral Statistics· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
venueaboutno affunlabeled
In defence of ‘non-adherence’
Peter Hutten-Czapski
2024· article· en· Canadian Journal of Rural Medicine· Economics, Econometrics and Finance
machine prediction:candidate · metaresearchconsensus · none
0
citations
afffundno abstractunlabeled
Determining the return on investment of a global adaptive platform trial for critically ill patients during COVID-19: A value of implementation analysis in low- and middle-income countries and globally
Alayna Carrandi, Abi Beane, Diptesh Aryal, Félix Camirand-Lemyre, Anaïs Charles‐Nelson, Barbara Wanjiru Citarella +11 more
2025· preprint· en· Research Square· Economics, Econometrics and Finance
machine prediction:candidate · metaresearchconsensus · none
0
citations
affno abstractunlabeled
AB1108 EFFECT OF GUSELKUMAB ADMINISTERED EVERY 8 WEEKS IN PATIENTS WITH ACTIVE PSORIATIC ARTHRITIS PERSISTS BETWEEN CONSECUTIVE DOSES AND IS DURABLE: POST HOC ANALYSIS OF A PHASE 3, RANDOMIZED, DOUBLE-BLIND, PLACEBO-CONTROLLED STUDY
Philip J. Mease, Xenofon Baraliakos, V. Chandran, Enrique R. Soriano, Peter Nash, Atul Deodhar +6 more
2023· article· en· Annals of the Rheumatic Diseases· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Utility in Health Studies
George W. Torrance
2005· other· en· Encyclopedia of Biostatistics· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations

How this was built: Screen · Findings · About