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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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Diversity and Career in Medicine
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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
aboutaboutness

The four routes compose: require the funder route and exclude affiliation to get the funder-only stratum no affiliation-based frame ever sees.

2,371 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.
2,371 works in the cohort · of 4,299,418page 38 of 48

Labels cover 16 of 2,371 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 2,371 of 2,371 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.

venueno affno abstractunlabeled
10.1016/s1541-9800(10)70283-0
2000· article· en· Time to knit· Social Sciences
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
aboutno affunlabeled
Doceo ergo sum: mentoring surgeons
2017· article· en· TSpace· Social Sciences
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
aboutno affunlabeled
Human participants research checklist.
2024· article· en· Figshare· Social Sciences
machine prediction:candidate · metaresearch+insufficient_payloadconsensus · none
0
citations
aboutno affunlabeled
Spotlight in Plastic Surgery: January 2021
Brett T. Phillips, Ali R. Abtahi, Saïd C. Azoury, Íris M. Brito, Joshua M. Cohen, Adam M. Goodreau +4 more
2020· article· en· Plastic & Reconstructive Surgery· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affaboutno abstractunlabeled
Team Canada: Academic Plastic Surgery Takes a Stand
Rob Harrop, Danny Peters, Lucie Lessard, Jason Williams, Jamie Bain, Peter Lennox +5 more
2018· article· en· Plastic Surgery· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
PD32-10 SETTING THE STANDARDS
Timothy Han, Lydia Glick, Joon Yau Leong, Seth Teplitsky, Rodrigo Noorani, Hanan Goldberg +8 more
2020· article· en· The Journal of Urology· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affvenueunlabeled
Engaging intersectionality in medical education
Princess Eze, Sarah Forgie, Philomina Okeke‐Ihejirika, Marghalara Rashid
2025· article· en· Canadian Medical Education Journal· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations

How this was built: Screen · Findings · About