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
Natural Language Processing Techniques
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.

3,084 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.
3,084 works in the cohort · of 4,299,418page 55 of 62

Labels cover 10 of 3,084 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 3,084 of 3,084 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.

aboutno affunlabeled
Gifted children: What and how to care?
2025· other· en· University of Ottawa - Library· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affno abstractunlabeled
Canadian Poetry and the Computational Concordance:
Sarah Roger, Paul M. Barrett, Kiera Obbard, Sandra Djwa
2023· book-chapter· en· Les Presses de l’Université d’Ottawa | University of Ottawa Press eBooks· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
venueno affunlabeled
Analysis on the Semantics of Word Trip
Min Lei
2011· article· en· Studies in literature and language· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Dataset of discussion threads from Meneame
Pablo Aragón, Vicenç Gómez, Andreas Kaltenbrunner
2019· dataset· en· Zenodo (CERN European Organization for Nuclear Research)· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
venueno affunlabeled
Thinking on WH-Movement
Xiamei Peng
2016· article· en· Canadian social science· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
afffundunlabeled
One Sense per Translation
Bradley Hauer, Grzegorz Kondrak
2023· preprint· en· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Lynx D2.5 Report on Lynx acquired vocabularies
Ilan Kernerman, Patricia Martín Chozas, Andis Lagzdiņš, Jorge Gracia
2019· article· en· Zenodo (CERN European Organization for Nuclear Research)· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Verb-Noun Compounds in Chinese
Ke Zou
2003· article· en· Southwest journal of linguistics· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
venueno affno abstractunlabeled
JIL: The Response
Stephen M. Watt
2013· article· en· Workplace· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
PoT-PTQ:Two-Step Power-of-Two Post-Training for LLMs
Xinyu Wang, Vahid Partovi Nia, Peng Lü, Xiao-Wen Chang, Boxing Chen
2025· book-chapter· Frontiers in artificial intelligence and applications· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
venueno affunlabeled
PolyU at TAC 2009.
You Ouyang, Wenjie Li
2009· article· en· Theory and applications of categories· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Du TAL au TIL
Michael Zock, Guy Lapalme
2012· preprint· en· arXiv (Cornell University)· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
venueno affno abstractunlabeled
LIA at TAC KBP 2012 English Entity Linking track.
Ludovic Bonnefoy, Patrice Bellot
2012· article· en· Theory and applications of categories· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations

How this was built: Screen · Findings · About