MétaCan
ENFR
Menu
Cohort builder

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.

Export CSVExport JSONAPI query

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.

Search term
Author
Year range
→
Sort
Language
Type
Field
Venue
Topic
Empathy and Medical Education
Retraction
Abstract
Evidence source
Study design
Label agreement
Label status

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.

1,896 results · 1 filter active ·
Results by year
20002025
Publication date
Categories
Machine labels · sparse coverage
Evidence
Language
Type
Citations
An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
1,896 works in the cohort · of 4,299,418page 10 of 38

Labels cover 5 of 1,896 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 1,896 of 1,896 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
Disabling the Body Politic
Christina Doonan
2021· article· en· Disability Studies Quarterly· Medicine
machine prediction:candidate · noneconsensus · none
9
citations
aboutno affunlabeled
Art of Oncology: New Voices Wanted
David P. Steensma
2011· editorial· en· Journal of Clinical Oncology· Medicine
machine prediction:candidate · noneconsensus · none
9
citations
affunlabeled
Empathy in paramedic practice: an overview
Lucy Kus, Lisa Henderson, Alan M Batt
2019· article· en· Journal of Paramedic Practice· Medicine
machine prediction:candidate · noneconsensus · none
9
citations
affunlabeled
Learning to live with being a physician
Marie T. Cave, D. Jean Clandinin
2007· article· en· Reflective Practice· Medicine
machine prediction:candidate · noneconsensus · none
8
citations
affunlabeled
Deconstructing Empathy
Raymond A. Mar
2011· article· en· Emotion Review· Medicine
machine prediction:candidate · noneconsensus · none
8
citations
aboutno affunlabeled
Medical humanity: how do we learn it?
Yifan Chang, Xiaoyi Zhou, Yan Zhang
2014· article· en· Chinese Medical Journal· Medicine
machine prediction:candidate · noneconsensus · none
8
citations
venueno affunlabeled
Medical humanities for what ails us
Allan Peterkin
2008· article· en· Canadian Medical Association Journal· Medicine
machine prediction:candidate · noneconsensus · none
8
citations
venueno affunlabeled
Pull of Words
Sarah Penwarden, Adrian Schoone
2021· article· en· Art/Research International A Transdisciplinary Journal· Medicine
machine prediction:candidate · noneconsensus · none
8
citations
← previousnext →

How this was built: Screen · Findings · About