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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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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
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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.

2,224 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.
2,224 works in the cohort · of 4,299,418page 44 of 45

Labels cover 25 of 2,224 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 2,224 of 2,224 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
Empowering Physiatrists In-Training to the Peer-Review Process
Allison N. Schroeder, Allison Bean, Martin E. Weaver, Patrick T. Spicer, Chan Gao, Walter R. Frontera +1 more
2018· article· en· American Journal of Physical Medicine & Rehabilitation· Medicine
machine prediction:candidate · metaresearchconsensus · metaresearch
0
citations
affunlabeled
Letters to the Editor
Alex G. Nagy
2002· article· en· Surgical Laparoscopy Endoscopy & Percutaneous Techniques· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affno abstractunlabeled
CQDM: Canada on the brain
Michael J. Haas
2014· article· en· Science-Business eXchange· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
venueno affunlabeled
Origine de la CIDIH
2023· article· fr· Aequitas Revue de développement humain handicap et changement social· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
venueno affunlabeled
MedBulletin
Yiming Zhang, Parnika Godkhindi, Aisling Zeng, Jia Du
2021· article· en· The Meducator· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
venueno affunlabeled
‘Dark Ages’ ahead for US scientists?
Roger Collier
2017· article· en· Canadian Medical Association Journal· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Doctors in love
Virginia P. Robinson
2002· article· en· Canadian Journal of Emergency Medicine· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
venueno affunlabeled
MedBulletin
Adrian Wong, Nuri Song
2022· article· en· The Meducator· Medicine
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
venueno affno abstractunlabeled
MedBulletin (Duplicate)
Keon Maleki, Ahmad Al-Khatib
2012· article· en· The Meducator· Medicine
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
venueno affno abstractunlabeled
MedBulletin (Duplicate)
Simone Liang, Randall Lau
2012· article· en· The Meducator· Medicine
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affno abstractunlabeled
From the scientific program chairs
Elizabeth M. Borycki, Niels Peek
2017· article· en· Research Explorer (The University of Manchester)· Medicine
machine prediction:candidate · noneconsensus · none
0
citations

How this was built: Screen · Findings · About