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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 Research Policy and Systems
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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
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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.

456 results · 1 filter active ·
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20032025
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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.
456 works in the cohort · of 4,299,418page 4 of 10

Labels cover 165 of 456 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 456 of 456 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.

affgemma · no categorygpt · no categorymodels split
Evidence in the learning organization
Gerald E. Crites, Megan McNamara, Elie A. Akl, W. Scott Richardson, Craig A. Umscheid, James Nishikawa
2009· article· en· Health Research Policy and Systems· Business, Management and Accounting
machine prediction:candidate · metaresearchconsensus · none
33
citations
affaboutgemma · no categorygpt · no categorymodels agree
Housing, income support and mental health: Points of disconnection
Cheryl Forchuk, Libbey Joplin, Ruth Schofield, Rick Csiernik, Carolyne Gorlick, Katy Turner
2007· article· en· Health Research Policy and Systems· Health Professions
machine prediction:candidate · noneconsensus · none
32
citations
afffundaboutgemma · no categorygpt · no categorymodels split
Key factors for national spread and scale-up of an eConsult innovation
Isabella Moroz, Douglas Archibald, Mylaine Breton, Élizabeth Côté-Boileau, Lois M. Crowe, Tanya Horsley +10 more
2020· article· en· Health Research Policy and Systems· Health Professions
machine prediction:candidate · noneconsensus · none
27
citations

How this was built: Screen · Findings · About