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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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Burn Injury Management and Outcomes
Retraction
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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.

898 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.
898 works in the cohort · of 4,299,418page 15 of 18

Labels cover 0 of 898 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 898 of 898 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
P90. Cost-Effective Care for Massive Burns
Pooja Yesantharao, Rahim Nazerali, Clifford C. Sheckter
2025· article· en· Plastic & Reconstructive Surgery Global Open· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
affaboutno abstractunlabeled
Burn data management and usage across Canada
Eduardo Gus, Jane Zhu, Thrmiga Sathiyamoorthy, Jennifer Zuccaro, Joel Fish
2023· article· en· Burns· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Chemical Burns
Robert Cartotto
2016· book-chapter· en· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Burns
Søren Loumann Nielsen
2001· book-chapter· en· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Opinion: Burn Survivors, You, and the ABA
Robert Cartotto
2025· article· en· Journal of Burn Care & Research· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
273 Social Exclusion and Pain Among Severe Burn Survivors
Rebeca Rios, Anne Marie Gehrke, S. E. Leventhal, Mohd Asif, Julie Caffrey, James A. Fauerbach
2018· article· en· Journal of Burn Care & Research· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
venueno affno abstractunlabeled
10.1016/j.ysur.2014.03.104
2000· article· en· Time to knit· Medicine
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
venueno affno abstractunlabeled
10.1016/j.yort.2015.04.065
2000· article· en· Time to knit· Medicine
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
affvenueunlabeled
Le solstice d'été de 2016
2016· article· fr· NPARC· Medicine
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affvenueunlabeled
Blowing dust
2018· article· en· NPARC· Medicine
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
venueno affno abstractunlabeled
10.1016/b978-0-323-42881-1.00035-3
2000· book-chapter· en· Time to knit· Medicine
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
affno abstractunlabeled
Burns and Heat Injury
Marc G. Jeschke
2024· other· en· Medicine
machine prediction:candidate · noneconsensus · none
0
citations

How this was built: Screen · Findings · About