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
Bacterial Infections and Vaccines
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.

1,642 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.
1,642 works in the cohort · of 4,299,418page 16 of 33

Labels cover 6 of 1,642 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 1,642 of 1,642 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.

affvenueaboutunlabeled
The Numbers Needed to Treat for Neurological Disorders
Miguel Bussière, Samuel Wiebe
2005· article· en· Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques· Immunology and Microbiology
machine prediction:candidate · noneconsensus · none
11
citations
afffundaboutunlabeled
Meningococcal vaccines in Canada: An update
MI Salvadori, Robert Bortolussi
2011· article· en· Paediatrics & Child Health· Immunology and Microbiology
machine prediction:candidate · noneconsensus · none
11
citations
affvenueaboutunlabeled
Epidemiology of invasive meningococcal disease in Canada, 2012–2019
Myriam Saboui, Raymond S. W. Tsang, Robert MacTavish, Amisha Agarwal, Y Anita Li, Marina I. Salvadori +1 more
2022· article· en· Canada Communicable Disease Report· Immunology and Microbiology
machine prediction:candidate · noneconsensus · none
11
citations
aboutno affunlabeled
Control of invasive meningococcal disease
Helen Marshall, Bing Wang, Steve Wesselingh, Matthew D. Snape, Andrew J. Pollard
2015· article· en· International Journal of Evidence-Based Healthcare· Immunology and Microbiology
machine prediction:candidate · noneconsensus · none
10
citations
affunlabeled
Vaccination during pregnancy.
Pina Bozzo, A Narducci, Adrienne Einarson
2011· article· en· PubMed· Immunology and Microbiology
machine prediction:candidate · noneconsensus · none
10
citations
afffundunlabeled
Safety and Immunogenicity of Two Doses of Quadrivalent Meningococcal Conjugate Vaccine or One Dose of Meningococcal Group C Conjugate Vaccine, both Administered Concomitantly with Routine Immunization to 12‐ to 18‐Month‐Old Children
Francisco Noya, Deirdre McCormack, Donna L. Reynolds, Dion Neame, Philipp Oster
2014· article· en· Canadian Journal of Infectious Diseases and Medical Microbiology· Immunology and Microbiology
machine prediction:candidate · noneconsensus · none
10
citations
affno abstractunlabeled
Meningococcal Vaccines
Andrew J. Pollard, Martin Maiden
2001· book· en· Humana Press eBooks· Immunology and Microbiology
machine prediction:candidate · noneconsensus · none
10
citations

How this was built: Screen · Findings · About