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
Authorship Attribution and Profiling
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.

216 results · 1 filter active ·
Results by year
20022025
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.
216 works in the cohort · of 4,299,418page 3 of 5

Labels cover 0 of 216 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 216 of 216 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
Sociolinguistics and programming
Fariha Naz, Jacqueline E. Rice
2015· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
4
citations
affunlabeled
Twitter-based gender recognition using transformers
Zahra Movahedi Nia, Ali Ahmadi, B. R. Mellado Garcia, James Orbinski, Ali Asgary, Jude Dzevela Kong
2023· article· en· Mathematical Biosciences & Engineering· Computer Science
machine prediction:candidate · noneconsensus · none
4
citations
affunlabeled
Authorship Attribution in Health Forums
Victoria Bobicev, Marina Sokolova, Khaled El Emam, Stan Matwin
2013· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
4
citations
affunlabeled
Digging into Digg
Luanne Freund, Justyna Berzowska, Jennifer Lee, Kevin Read, Heidi Schiller
2011· article· en· Proceedings of the 2011 iConference· Computer Science
machine prediction:candidate · noneconsensus · none
3
citations
affno abstractunlabeled
Genre-ous: The Movie Genre Detector
Amr Shahin, Adam Krzyżak
2020· book-chapter· en· Communications in computer and information science· Computer Science
machine prediction:candidate · noneconsensus · none
3
citations
venueno affunlabeled
<i>Reflections</i>
Corrinne Harol, Brynn Lewis, Subhash R. Lele
2019· article· en· Eighteenth-Century Fiction· Computer Science
machine prediction:candidate · noneconsensus · none
3
citations
affno abstractunlabeled
Knowledge Discovery in Adversarial Settings
David B. Skillicorn
2012· book-chapter· en· Intelligent systems reference library· Computer Science
machine prediction:candidate · noneconsensus · none
1
citations
affunlabeled
Machines and Humans, Schemes and Tropes
Michael Ullyot, Adam Bradley
2018· article· en· Early modern literary studies· Computer Science
machine prediction:candidate · noneconsensus · none
1
citations
aboutno affunlabeled
The Corpus for Idiolectal Research (CIDRE)
Olga Seminck, Philippe Gambette, Dominique Legallois, Thierry Poibeau
2021· article· en· Journal of Open Humanities Data· Computer Science
machine prediction:candidate · noneconsensus · none
1
citations
affunlabeled
ICSPIS 2023 Keynote Speakers
Keynote Speaker, C Benjamin
2023· article· en· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affunlabeled
ICSPIS 2023 Full Program
Benjamin C. M. Fung, C Benjamin, Bashar Kilani, Khalid Yaqoob, Marshall Stephen
2023· article· en· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations

How this was built: Screen · Findings · About