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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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Implementation Science Communications
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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.

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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.

98 results · 1 filter active ·
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20202025
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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.
98 works in the cohort · of 4,299,418page 1 of 2

Labels cover 6 of 98 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 98 of 98 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.

affgpt · no categorygrok · metaresearch+metaepi_broadopus · no categorymodels split
Advancing the pragmatic measurement of sustainment: a narrative review of measures
Joanna C. Moullin, Marisa Sklar, Amy Green, Kelsey S. Dickson, Nicole A. Stadnick, Kendal Reeder +1 more
2020· review· en· Implementation Science Communications· Health Professions
machine prediction:candidate · metaresearchconsensus · none
86
citations
afffundunlabeled
Building capacity for implementation—the KT Challenge
Agnes Black, Marla Steinberg, Amanda E. Chisholm, Kristi Coldwell, Alison M. Hoens, Jiak Chin Koh +4 more
2021· article· en· Implementation Science Communications· Health Professions
machine prediction:candidate · noneconsensus · none
31
citations
affunlabeled
Applying implementation science frameworks to identify factors that influence the intention of healthcare providers to offer PrEP care and advocate for PrEP in HIV clinics in Colombia: a cross-sectional study
Jorge Martínez-Cajas, Julián Andrés Torres-Isasiga, Héctor Fabio Mueses-Marín, Pilar Camargo‐Plazas, Marcela Arrivillaga, Sheila Andrea Gómez +3 more
2022· article· en· Implementation Science Communications· Medicine
machine prediction:candidate · noneconsensus · none
14
citations

How this was built: Screen · Findings · About