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
Reading and Literacy Development
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.

2,605 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.
2,605 works in the cohort · of 4,299,418page 49 of 53

Labels cover 2 of 2,605 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 2,605 of 2,605 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.

affno abstractunlabeled
Reading Skills
Elizabeth Levin, Leslie Villeneuve
2011· book-chapter· en· Psychology
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Reading & Writing
2005· article· en· Language Teaching· Psychology
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
aboutno affunlabeled
la déesse des mouches à feu pdf gratuit
2024· other· fr· Zenodo (CERN European Organization for Nuclear Research)· Psychology
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
venueno affno abstractunlabeled
10.1016/j.bjorlp.2021.05.014
Maristela Júlio Costa, Sinéia Neujahr dos Santos, Eliane Schochat
2000· article· en· Time to knit· Psychology
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
affno abstractunlabeled
Reading
Elizabeth Levin, Leslie Villeneuve
2011· book-chapter· en· Psychology
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affunlabeled
Early spelling and grammar
Dominic Wyse, Christine Parker
2012· article· en· Primary Teacher Update· Psychology
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Teaching Vocabulary Effectively to Kindergarteners
Gloria Ramírez, Manjeet Gupta
2019· article· en· 2019 Conference of the Canadian Society for the Study of Education· Psychology
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Language disorders and reading acquisition
Stéphanie Ducrot, Noël Nguyen
2003· preprint· en· HAL (Le Centre pour la Communication Scientifique Directe)· Psychology
machine prediction:candidate · noneconsensus · none
0
citations
venueno affunlabeled
Phonemic awareness
Michael Carey
2025· book-chapter· en· Language and Literacy· Psychology
machine prediction:candidate · noneconsensus · none
0
citations

How this was built: Screen · Findings · About