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
Software System Performance and Reliability
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.

1,099 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.
1,099 works in the cohort · of 4,299,418page 13 of 22

Labels cover 1 of 1,099 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 1,099 of 1,099 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
Resilient Network Design
Yousef S. Kavian, Habib F. Rashvand, Bin Wang, Hussein T. Mouftah
2013· article· en· IET Networks· Computer Science
machine prediction:candidate · noneconsensus · none
1
citations
affunlabeled
Dendrite
Brad Glasbergen, Fangyu Wu, Khuzaima Daudjee
2021· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
1
citations
afffundunlabeled
Sampling-based program execution monitoring
Sebastian Fischmeister, Yanmeng Ba
2010· article· en· ACM SIGPLAN Notices· Computer Science
machine prediction:candidate · noneconsensus · none
1
citations
affunlabeled
SelfTalk for Dena
Saeed Ghanbari, Gokul Soundararajan, Cristiana Amza
2010· article· en· ACM SIGOPS Operating Systems Review· Computer Science
machine prediction:candidate · noneconsensus · none
1
citations
affunlabeled
Focused Layered Performance Modelling by Aggregation
Farhana Islam, Dorina C. Petriu, Murray Woodside
2022· article· en· ACM Transactions on Modeling and Performance Evaluation of Computing Systems· Computer Science
machine prediction:candidate · noneconsensus · none
1
citations
affunlabeled
A DDMRP implementation user feedbacks and stakes analysis
Guillaume Dessevre, Jacques Lamothe, Vincent Pomponne, Pierre Baptiste, Matthieu Lauras, Robert Pellerin
2020· preprint· en· PolyPublie (École Polytechnique de Montréal)· Computer Science
machine prediction:candidate · noneconsensus · none
1
citations
affunlabeled
Securing Agentic AI in IoT Systems
Sandra Kumi, Richard K. Lomotey, Ralph Deters
2025· article· Computer Science
machine prediction:candidate · noneconsensus · none
1
citations

How this was built: Screen · Findings · About