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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 and Medical Research Impacts
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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.

2,224 results · 1 filter active ·
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20002025
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Machine labels · sparse coverage
Evidence
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An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
2,224 works in the cohort · of 4,299,418page 18 of 45

Labels cover 25 of 2,224 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 2,224 of 2,224 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.

venueaboutno affunlabeled
A new paradigm for health research funding
Paul Webster
2013· article· en· Canadian Medical Association Journal· Medicine
machine prediction:candidate · metaresearchconsensus · none
2
citations
affaboutunlabeled
The Innovation Forager
Thomas Ungar, Madalyn Marcus
2014· letter· en· Academic Medicine· Medicine
machine prediction:candidate · noneconsensus · none
2
citations
venueno affunlabeled
Where philosophy meets clinical science
Natale Gaspare De Santo, Rosa Maria De Santo, Alessandra Perna, Carmela Bisaccia, Rado Pišot, Massimo Círillo
2011· article· en· Hemodialysis International· Medicine
machine prediction:candidate · noneconsensus · none
2
citations
venueno affunlabeled
The "battle" against cancer
P. J. Byrne
2011· letter· en· Canadian Medical Association Journal· Medicine
machine prediction:candidate · noneconsensus · none
2
citations
venueno affunlabeled
A new year and new opportunities
P. C. Hebert
2006· article· en· Canadian Medical Association Journal· Medicine
machine prediction:candidate · noneconsensus · none
1
citations
venueno affno abstractunlabeled
Academic designations for the modern age
P Ravi Shankar
2023· article· en· Canadian Medical Education Journal· Medicine
machine prediction:candidate · noneconsensus · none
1
citations
affno abstractunlabeled
Who wants yesterday’s papers?
Heiko Heerklotz
2023· editorial· en· Biophysical Journal· Medicine
machine prediction:candidate · scholarly_communicationconsensus · none
1
citations
affvenueunlabeled
Benefits of Membership
Richard N. Fedorak
2000· article· en· Canadian Journal of Gastroenterology· Medicine
machine prediction:candidate · noneconsensus · none
1
citations
affvenueunlabeled
Research and residency match: a near-peer online webinar
Justin-Pierre Lorange, Anne Xuan-Lan Nguyen, Jobanpreet Dhillon, Caroline Najjar
2022· article· en· Canadian Medical Education Journal· Medicine
machine prediction:candidate · noneconsensus · none
1
citations
aboutno affunlabeled
SPEECH: Seize the Day!
David T. Wong
2010· article· en· Journal of Dental Research· Medicine
machine prediction:candidate · insufficient_payloadconsensus · none
1
citations

How this was built: Screen · Findings · About