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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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Vaccine Coverage and Hesitancy
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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.

3,295 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.
3,295 works in the cohort · of 4,299,418page 22 of 66

Labels cover 28 of 3,295 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 3,295 of 3,295 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.

aboutno affunlabeled
COVID-19 vaccine hesitancy in India
Arjun Singh, Pankaj Chaturvedi
2021· article· en· Cancer Research Statistics and Treatment· Social Sciences
machine prediction:candidate · noneconsensus · none
9
citations
afffundvenueno abstractunlabeled
Vaccine coverage of children in care of the child welfare system
Jennifer Hermann, Kimberley Simmonds, Christopher Bell, Ellen Rafferty, Shannon E. MacDonald
2018· article· en· Canadian Journal of Public Health· Social Sciences
machine prediction:candidate · noneconsensus · none
9
citations
affunlabeled
Access to Vaccines: A Call to Action
Noni E. MacDonald, Joanne Embreé
2003· article· en· Canadian Journal of Infectious Diseases and Medical Microbiology· Social Sciences
machine prediction:candidate · noneconsensus · none
9
citations
venueaboutno affunlabeled
Closing Canada’s COVID-19 vaccination gap
Diana Duong
2021· article· en· Canadian Medical Association Journal· Social Sciences
machine prediction:candidate · noneconsensus · none
9
citations
afffundvenueno abstractunlabeled
Pharmacists as immunizers to <u>Improve</u> coverage and provider/recipient satisfaction: <u>A</u> prospective, <u>C</u> ontrolled <u>C</u> ommunity <u>E</u> mbedded <u>S</u> tudy with vaccine <u>S</u> with low coverage rates (the Improve ACCESS Study): Study summary and anticipated significance
Jennifer E. Isenor, Melissa Kervin, Beth Halperin, Joanne M. Langley, Julie A. Bettinger, Karina A. Top +8 more
2020· article· en· Canadian Pharmacists Journal / Revue des Pharmaciens du Canada· Social Sciences
machine prediction:candidate · noneconsensus · none
9
citations
aboutno affunlabeled
Immunization Update 2005: Stepping Forward
Noni E. MacDonald
2005· article· en· Canadian Journal of Infectious Diseases and Medical Microbiology· Social Sciences
machine prediction:candidate · noneconsensus · none
9
citations

How this was built: Screen · Findings · About