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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.

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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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Survey Methodology and Nonresponse
Retraction
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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
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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.

587 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.
587 works in the cohort · of 4,299,418page 2 of 12

Labels cover 14 of 587 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 587 of 587 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.

afffundunlabeled
Addressing Nonresponse Bias in Postal Surveys
Shannon E. MacDonald, Christine V. Newburn‐Cook, Donald Schopflocher, Solina Richter
2008· article· en· Public Health Nursing· Social Sciences
machine prediction:candidate · metaresearchconsensus · metaresearch
56
citations
affunlabeled
Response rates for surveys of chiropractors
Monica Russell, Marja J. Verhoef, H. Stephen Injeyan, D. Gordon McMorland
2004· article· en· Journal of Manipulative and Physiological Therapeutics· Social Sciences
machine prediction:candidate · metaresearchconsensus · none
52
citations
afffundaboutunlabeled
Quality of reporting of surveys in critical care journals
Mark Duffett, Karen E. A. Burns, Neill K. J. Adhikari, Donald M. Arnold, François Lauzier, Michelle E. Kho +6 more
2011· review· en· Critical Care Medicine· Social Sciences
machine prediction:candidate · metaresearchconsensus · metaresearch
47
citations
venueno affunlabeled
Evaluation of Electronic and Paper-Pen Data Capturing Tools for Data Quality in a Public Health Survey in a Health and Demographic Surveillance Site, Ethiopia: Randomized Controlled Crossover Health Care Information Technology Evaluation
Atinkut Alamirrew Zeleke, Adina Demissie, Fabian Otto‐Sobotka, Marc Wilken, Myriam Lipprandt, Binyam Tilahun +1 more
2018· article· en· JMIR mhealth and uhealth· Social Sciences
machine prediction:candidate · metaresearchconsensus · none
43
citations
affno abstractunlabeled
Web-Based Survey
R. Michael Alvarez, Carla VanBeselaere
2005· book-chapter· en· Encyclopedia of Social Measurement· Social Sciences
machine prediction:candidate · metaresearchconsensus · none
31
citations
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