MétaCan
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.

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
Homelessness and Social Issues
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.

4,406 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.
4,406 works in the cohort · of 4,299,418page 59 of 89

Labels cover 16 of 4,406 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 4,406 of 4,406 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
Homelessness
Lois M. Takahashi
2014· reference-entry· en· Geography· Health Professions
machine prediction:candidate · noneconsensus · none
1
citations
aboutno affunlabeled
The Development of Probation Services in Ontario
George G. McFarlane, Daniel W. F. Coughlan, Alfred A. Sumpter
2013· dataset· en· PsycEXTRA Dataset· Health Professions
machine prediction:candidate · noneconsensus · none
1
citations
affaboutunlabeled
Invisiblizing Trans Homelessness
Alex Withers
2024· article· en· Atlantis Critical Studies in Gender Culture & Social Justice· Health Professions
machine prediction:candidate · noneconsensus · none
1
citations
affaboutunlabeled
Place of residence and maternal health behaviours
Wendy Sword, John Eyles, Patrick F. DeLuca, Maureen Heaman, Dawn Kingston, Sonia Buist +2 more
2015· article· en· European Journal of Public Health· Health Professions
machine prediction:candidate · noneconsensus · none
1
citations
affaboutno abstractunlabeled
Homelessness in North Bay, Ontario, Canada
Henri Pallard, Carol Kauppi, Kathy King, Katrina Srigley
2015· article· en· SSRN Electronic Journal· Health Professions
machine prediction:candidate · noneconsensus · none
1
citations
afffundunlabeled
Associations Between Extreme Weather Events and Resource Insecurities With HIV Vulnerabilities and Biomedical HIV Prevention Outcomes Among Adolescent Girls and Young Women in Kenya: A Cross-Sectional Analysis
Carmen H. Logie, Zerihun Admassu, Aryssa Hasham, Humphres Evelia, Julia Kagunda, Beldine Omondi +6 more
2025· article· en· Journal of the International Association of Providers of AIDS Care (JIAPAC)· Health Professions
machine prediction:candidate · noneconsensus · none
1
citations
venueno affunlabeled
Australian Prisons Are Failing Prisoners
Renee McNab
2024· article· en· Journal of Prisoners on Prisons· Health Professions
machine prediction:candidate · noneconsensus · none
1
citations
venueno affunlabeled
Outcomes for Māori participants in Housing First
Jenny Ombler, Tīria Pehi, Saera Chun, Keri Lawson-Te Aho, Terence Jiang, Nevil Pierse
2025· article· en· International Indigenous Policy Journal· Health Professions
machine prediction:candidate · noneconsensus · none
1
citations

How this was built: Screen · Findings · About