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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 Safety and Medication Errors
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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.

1,743 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.
1,743 works in the cohort · of 4,299,418page 27 of 35

Labels cover 12 of 1,743 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 1,743 of 1,743 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
Medical errors can cost lives
Consolato Sergi
2024· article· en· Archives of Medical Science· Health Professions
machine prediction:candidate · noneconsensus · none
1
citations
venueno affno abstractunlabeled
ACEN and the Health of Canadians
Heather Mass
2008· article· en· Nursing leadership· Health Professions
machine prediction:candidate · noneconsensus · none
1
citations
affvenueunlabeled
Patient safety and “medical error”
W. Ward Flemons
2013· article· en· Canadian Medical Association Journal· Health Professions
machine prediction:candidate · noneconsensus · none
1
citations
affunlabeled
Introduction to Patient Safety
Matt McMillan, Daniel Pang
2024· other· en· Health Professions
machine prediction:candidate · noneconsensus · none
1
citations
aboutno affunlabeled
Medical Errors: Next Steps
Arnauld Nicogossian, Bonnie Stabile, Otmar Kloiber, Thomas Zimmerman
2016· article· en· World Medical & Health Policy· Health Professions
machine prediction:candidate · noneconsensus · none
1
citations
aboutno affunlabeled
Applying Human Factors Methods to Improve Healthcare Risk Management Tools
Carleene Bañez, J. Brett Carruthers, Stefano Gelmi, Arlene Kraft, Catherine Gaulton, Trevor Hall
2021· article· en· Proceedings of the International Symposium on Human Factors and Ergonomics in Health Care· Health Professions
machine prediction:candidate · noneconsensus · none
1
citations
venueno affunlabeled
10.51847/SLjk9aHpMe
G P Mohanta
2000· article· en· Time to knit· Health Professions
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
1
citations
aboutno affunlabeled
An Opportunity for Reflection
G. Ross Baker
2014· article· en· Healthcare Quarterly· Health Professions
machine prediction:candidate · noneconsensus · none
1
citations
aboutno affunlabeled
Graduate Medical Education and Patient Safety
Kaveh G Shojania, Kathlyn E. Fletcher, Sanjay Saint
2007· article· en· Annals of Internal Medicine· Health Professions
machine prediction:candidate · insufficient_payloadconsensus · none
1
citations

How this was built: Screen · Findings · About