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
Personal Information Management and User Behavior
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.

465 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.
465 works in the cohort · of 4,299,418page 3 of 10

Labels cover 5 of 465 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 465 of 465 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.

affunlabeled
Countdown Timer Speed
Moojan Ghafurian, David Reitter, Frank E. Ritter
2020· article· en· ACM Transactions on Computer-Human Interaction· Decision Sciences
machine prediction:candidate · noneconsensus · none
23
citations
aboutno affunlabeled
Information overload in literature
Sebastian Groes
2016· article· en· Textual Practice· Decision Sciences
machine prediction:candidate · noneconsensus · none
22
citations
afffundunlabeled
BIGFile
Wanyu Liu, Olivier Rioul, Joanna McGrenere, Wendy E. Mackay, Michel Beaudouin-Lafon
2018· preprint· en· Decision Sciences
machine prediction:candidate · insufficient_payloadconsensus · none
21
citations
afffundunlabeled
Everyday serendipity as described in social media
Victoria L. Rubin, Jacquelyn Burkell, Anabel Quan‐Haase
2010· article· en· Proceedings of the American Society for Information Science and Technology· Decision Sciences
machine prediction:candidate · noneconsensus · none
21
citations
affunlabeled
OpenMessenger
Jeremy Birnholtz, Carl Gutwin, Gonzalo Ramos, Mark Watson
2008· article· en· Decision Sciences
machine prediction:candidate · noneconsensus · none
20
citations
affunlabeled
AuraOrb
Mark Altosaar, Roel Vertegaal, Changuk Sohn, Daniel Cheng
2006· article· en· Decision Sciences
machine prediction:candidate · insufficient_payloadconsensus · none
20
citations
affunlabeled
AuraOrb
Mark Altosaar, Roel Vertegaal, Changuk Sohn, Daniel Cheng
2006· article· en· Decision Sciences
machine prediction:candidate · noneconsensus · none
18
citations
affunlabeled
Design for Collaborative Information-Seeking
Sung-Soo Hong, Minhyang Suh, Tae Soo Kim, Irina Smoke, Sang-Wha Sien, Janet Ng +2 more
2019· article· en· Proceedings of the ACM on Human-Computer Interaction· Decision Sciences
machine prediction:candidate · noneconsensus · none
18
citations
affunlabeled
What's in people's digital file collections?
Jesse David Dinneen, Charles‐Antoine Julien
2019· article· en· Proceedings of the Association for Information Science and Technology· Decision Sciences
machine prediction:candidate · noneconsensus · none
18
citations
affunlabeled
Mailing Archived Emails as Postcards
David B. Gerritsen, Dan Tasse, Jennifer K. Olsen, Tatiana A. Vlahovic, Rebecca Gulotta, William Odom +2 more
2016· article· en· Decision Sciences
machine prediction:candidate · noneconsensus · none
17
citations
aboutno affunlabeled
La perception de la confiance informationnelle
Dominique Maurel, Aïda Chebbi
2012· article· fr· Communication et organisation· Decision Sciences
machine prediction:candidate · noneconsensus · none
16
citations
affunlabeled
PaperSpace
Jeff Smith, Jeremy Long, Tanya Lung, Mohd Anwar, Sriram Subramanian
2006· article· en· Decision Sciences
machine prediction:candidate · noneconsensus · none
14
citations
affunlabeled
Understanding and supporting multi‐session web tasks
Bonnie MacKay, Carolyn Watters
2008· article· en· Proceedings of the American Society for Information Science and Technology· Decision Sciences
machine prediction:candidate · noneconsensus · none
14
citations
affunlabeled
Determining relevancy
Thomas Fritz, Gail C. Murphy
2011· article· en· Decision Sciences
machine prediction:candidate · noneconsensus · none
14
citations
affunlabeled
A Scale for Measuring Email Overload
Bernie Hogan, Danyel Fisher
2006· article· en· Health care law monthly· Decision Sciences
machine prediction:candidate · noneconsensus · none
12
citations

How this was built: Screen · Findings · About