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
Skin Protection and Aging
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.

796 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.
796 works in the cohort · of 4,299,418page 4 of 16

Labels cover 0 of 796 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 796 of 796 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.

affaboutunlabeled
Ultraviolet radiation.
Richard P. Gallagher, Tim K. Lee, Chris Bajdik, Marilyn J. Borugian
2010· article· en· PubMed· Medicine
machine prediction:candidate · insufficient_payloadconsensus · none
31
citations
affno abstractunlabeled
Use of hair colouring products and breast cancer risk
Tongzhang Zheng, Theodore R. Holford, S. T. Mayne, Patricia H. Owens, Peter Boyle, B Zhang +2 more
2002· article· en· European Journal of Cancer· Medicine
machine prediction:candidate · noneconsensus · none
28
citations
aboutno affunlabeled
The Conjunctivitis of Solar (Actinic) Prurigo
Mario Magaña, Yira Mendez, Abelardo Rodriguez, Manuel Mascott
2000· article· en· Pediatric Dermatology· Medicine
machine prediction:candidate · noneconsensus · none
28
citations
affno abstractunlabeled
Solarium use in Australia, recent trends and context
Kate Francis, Suzanne Dobbinson, Melanie Wakefield, Afaf Girgis
2010· article· en· Australian and New Zealand Journal of Public Health· Medicine
machine prediction:candidate · noneconsensus · none
27
citations
fundno affunlabeled
Variation in the activities of late stage filaggrin processing enzymes, calpain‐1 and bleomycin hydrolase, together with pyrrolidone carboxylic acid levels, corneocyte phenotypes and plasmin activities in non‐sun‐exposed and sun‐exposed facial stratum corneum of different ethnicities
N. Raj, R. Voegeli, Anthony V. Rawlings, Beverley Summers, Michael R. Munday, Majella E. Lane
2016· article· en· International Journal of Cosmetic Science· Medicine
machine prediction:candidate · noneconsensus · none
25
citations
affaboutno abstractunlabeled
Predictors of Sunburn among Canadian Adults
Mark P. Purdue, Loraine D. Marrett, L Peters, Jason K. Rivers
2001· article· en· Preventive Medicine· Medicine
machine prediction:candidate · noneconsensus · none
23
citations
venueaboutno affunlabeled
Vitamin D and Sun Exposure: A Community Survey in Australia
Vu Tran, Monika Janda, Robyn Lucas, Donald S.A. McLeod, Bridie S. Thompson, Mary Waterhouse +2 more
2023· article· en· Current Oncology· Medicine
machine prediction:candidate · noneconsensus · none
22
citations
← previousnext →

How this was built: Screen · Findings · About