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
Canadian acoustics
Topic
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.

1,875 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.
1,875 works in the cohort · of 4,299,418page 32 of 38

Labels cover 1 of 1,875 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 1,875 of 1,875 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.

affvenueno abstractunlabeled
Your new president speaking
Jérémie Voix
2017· article· en· Canadian acoustics· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affvenueunlabeled
Is my material an efficient acoustical material
Olivier Doutres, Franck Sgard, Frédéric Laville, Jérémie Voix, Olivier Bouthot, Hugues Nélisse +2 more
2015· article· en· Canadian acoustics· Engineering
machine prediction:candidate · noneconsensus · none
0
citations
venueaboutno affunlabeled
Noise Impact - Wind Farms in Quebec
Martin Meunier
2015· article· en· Canadian acoustics· Engineering
machine prediction:candidate · noneconsensus · none
0
citations
affvenueno abstractunlabeled
Post-conference report on AWC 2016
M. Kathleen Pichora Fuller
2016· article· en· Canadian acoustics· Engineering
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affvenueaboutunlabeled
Joint Standards meeting - 2010 - Minutes
Tim Kelsall
2010· article· en· Canadian acoustics· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
venueno affunlabeled
Audio for committee rooms
Jeff Bamford
2004· article· en· Canadian acoustics· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
venueno affunlabeled
Hatch Noise and Vibration
Tim Kelsall
2016· article· en· Canadian acoustics· Engineering
machine prediction:candidate · noneconsensus · none
0
citations
← previousnext →

How this was built: Screen · Findings · About