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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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Patient-Provider Communication in Healthcare
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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.

2,296 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.
2,296 works in the cohort · of 4,299,418page 21 of 46

Labels cover 24 of 2,296 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 2,296 of 2,296 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
Microanalysis of Clinical Interaction (MCI)
Jennifer Gerwing, Sara Healing, Julia Menichetti
2023· book-chapter· en· Pragmatics & beyond. New series· Health Professions
machine prediction:candidate · noneconsensus · none
13
citations
affno abstractunlabeled
The birth of @ISNeducation
Tejas Desai, Arvind Conjeevaram, Omar Taco, Sanjeev Nair, Sivakumar Sridharan, Rolando Claure‐Del Granado +19 more
2017· editorial· en· Kidney International· Health Professions
machine prediction:candidate · noneconsensus · none
13
citations
affunlabeled
Decision aids in anesthesia: do they help?
Warren A. Southerland, Leah Beight, Fred E. Shapiro, Richard D. Urman
2020· review· en· Current Opinion in Anaesthesiology· Health Professions
machine prediction:candidate · noneconsensus · none
13
citations

How this was built: Screen · Findings · About