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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.

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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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Healthcare professionals’ stress and burnout
Retraction
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Study design
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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
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venuejournal
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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.

1,945 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.
1,945 works in the cohort · of 4,299,418page 25 of 39

Labels cover 8 of 1,945 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 1,945 of 1,945 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.

affvenueaboutunlabeled
Les défis auxquels ont fait face les membres de l’Équipe de la Défense du Canada au début de la pandémie : principales conclusions du sondage de l’Équipe de la Défense sur la COVID-19
Jennifer E. C. Lee, Irina Goldenberg, Ann-Renée Blais, Caitlin Comeau, Carina Daugherty, Eva Guérin +6 more
2022· article· fr· Promotion de la santé et prévention des maladies chroniques au Canada· Health Professions
machine prediction:candidate · noneconsensus · none
2
citations
affunlabeled
When I say … wellness
Aliya Kassam, Maria Athina Martimianakis
2023· letter· en· Medical Education· Health Professions
machine prediction:candidate · noneconsensus · none
2
citations
affunlabeled
Calling for a Multi-Level Green Healthcare Ethics
Valentina de Maack, Clara Tardif, Nathalie Clavel, Charles Dupras
2025· letter· en· The American Journal of Bioethics· Health Professions
machine prediction:candidate · noneconsensus · none
2
citations
affaboutunlabeled
“The Cost in the Individual”
Kenneth Lee, Quynh Doan, Graham C. Thompson, Ash Sandhu, Jeffrey N. Bone, Daniel K. Ting
2023· article· en· Pediatric Emergency Care· Health Professions
machine prediction:candidate · noneconsensus · none
2
citations
affunlabeled
Addressing burnout in surgery and vascular surgery
Rebecca Lozano-Franco, Nardin Farag, Cedric Keutcha Kamani, Rita Mancini, Kristina Shanahan, Dawn M. Coleman +1 more
2024· article· en· JVS-Vascular Insights· Health Professions
machine prediction:candidate · noneconsensus · none
2
citations
affvenueno abstractunlabeled
Before it becomes completely random
Assil Abda, Jean‐Michel Leduc, Geneviève Benoît, C Hervouet-Zeiber
2022· article· en· Canadian Medical Education Journal· Health Professions
machine prediction:candidate · noneconsensus · none
2
citations
affunlabeled
PA job satisfaction
James F. Cawley
2024· review· en· JAAPA· Health Professions
machine prediction:candidate · noneconsensus · none
2
citations
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How this was built: Screen · Findings · About