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
Memory Processes and Influences
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.

1,529 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.
1,529 works in the cohort · of 4,299,418page 5 of 31

Labels cover 4 of 1,529 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 1,529 of 1,529 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.

afffundunlabeled
Distraction Can Reduce Age-Related Forgetting
Renée K. Biss, K. W. Joan Ngo, Lynn Hasher, Karen L. Campbell, Gillian Rowe
2013· article· en· Psychological Science· Neuroscience
machine prediction:candidate · noneconsensus · none
61
citations
afffundunlabeled
Females Scan More Than Males
Jennifer J. Heisz, Molly Pottruff, David I. Shore
2013· article· en· Psychological Science· Neuroscience
machine prediction:candidate · noneconsensus · none
60
citations
afffundunlabeled
Directed forgetting: Comparing pictures and words.
Chelsea K. Quinlan, Tracy Taylor, Jonathan M. Fawcett
2010· article· en· Canadian Journal of Experimental Psychology/Revue canadienne de psychologie expérimentale· Neuroscience
machine prediction:candidate · noneconsensus · none
60
citations
afffundno abstractunlabeled
The spacing effect stands up to big data
Ah-Leum Sol Kim, Audrey Wong-Kee-You, Melody Wiseheart, R. Shayna Rosenbaum
2019· article· en· Behavior Research Methods· Neuroscience
machine prediction:candidate · noneconsensus · none
59
citations
afffundunlabeled
Creating a recollection-based memory through drawing.
Jeffrey D. Wammes, Melissa E. Meade, Myra A. Fernandes
2017· article· en· Journal of Experimental Psychology Learning Memory and Cognition· Neuroscience
machine prediction:candidate · noneconsensus · none
57
citations

How this was built: Screen · Findings · About