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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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Social Media in Health Education
Retraction
Abstract
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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.

2,014 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.
2,014 works in the cohort · of 4,299,418page 35 of 41

Labels cover 32 of 2,014 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 2,014 of 2,014 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
JDNA Updates
Angela L. Borger
2023· article· en· Journal of the Dermatology Nurses’ Association· Social Sciences
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affvenueno abstractunlabeled
Patient information vs. The Algorithm
Michael Leveridge
2024· article· en· Canadian Urological Association Journal· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
51 PedsCases Quality Improvement User Survey
Amarjot Padda, Chris Novak, Peter Gill, Larissa Shapka, Melanie Lewis, Karen Forbes
2019· article· en· Paediatrics & Child Health· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affaboutunlabeled
CAN‐THUMBS UP: Recruitment in the Virtual Era
Haakon B. Nygaard, Penelope Slack, Howard Feldman, Howard Chertkow, Sylvie Belleville, Manuel Montero‐Odasso +13 more
2023· article· en· Alzheimer s & Dementia· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Cyberspace Chat…
William M. Parsley
2000· article· en· International Society of Hair Restoration Surgery· Social Sciences
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affno abstractunlabeled
[no title]
Rachel A Oommen, Fabian Schwarz
2017· article· fr· PubMed· Social Sciences
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
aboutno affunlabeled
AJN On the Cover
2023· article· en· AJN American Journal of Nursing· Social Sciences
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
venueno affunlabeled
Unmoderated Posters: Education
CUAJ Editorial
2014· article· en· Canadian Urological Association Journal· Social Sciences
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affunlabeled
The Scalpel Is Passed
Tracey S. Corey
2022· article· en· American Journal of Forensic Medicine & Pathology· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
EDITORIAL COMMENT
John Z. Benton, Christopher J.D. Wallis, Zachary Klaassen
2022· editorial· es· Urology· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations

How this was built: Screen · Findings · About