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
IEEE Communications Surveys & Tutorials
Topic
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.

206 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.
206 works in the cohort · of 4,299,418page 2 of 5

Labels cover 0 of 206 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 206 of 206 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
Load Balancing in Data Center Networks: A Survey
Jiao Zhang, F. Richard Yu, Shuo Wang, Tao Huang, Zengyi Liu, Yunjie Liu
2018· article· en· IEEE Communications Surveys & Tutorials· Computer Science
machine prediction:candidate · noneconsensus · none
178
citations
affunlabeled
A Tutorial on Movable Antennas for Wireless Networks
Lipeng Zhu, Wenyan Ma, Weidong Mei, Yong Zeng, Qingqing Wu, Boyu Ning +4 more
2025· article· en· IEEE Communications Surveys & Tutorials· Engineering
machine prediction:candidate · noneconsensus · none
132
citations
afffundunlabeled
Intrusion Detection Systems: A Cross-Domain Overview
Lionel Nganyewou Tidjon, Marc Frappier, Amel Mammar
2019· article· en· IEEE Communications Surveys & Tutorials· Computer Science
machine prediction:candidate · noneconsensus · none
128
citations
affunlabeled
Stochastic Information Management in Smart Grid
Hao Liang, Amit Kumar Tamang, Weihua Zhuang, Xuemin Shen
2014· article· en· IEEE Communications Surveys & Tutorials· Engineering
machine prediction:candidate · noneconsensus · none
113
citations
affunlabeled
Semantics-Empowered Communications: A Tutorial-Cum-Survey
Zhilin Lu, Rongpeng Li, Kun Lü, Xianfu Chen, Ekram Hossain, Zhifeng Zhao +1 more
2023· article· en· IEEE Communications Surveys & Tutorials· Computer Science
machine prediction:candidate · noneconsensus · none
96
citations
affunlabeled
Localization Prediction in Vehicular Ad Hoc Networks
Leandro N. Balico, Antônio A. F. Loureiro, Eduardo F. Nakamura, Raimundo Barreto, Richard W. Pazzi, Horácio A.B.F. Oliveira
2018· article· en· IEEE Communications Surveys & Tutorials· Engineering
machine prediction:candidate · noneconsensus · none
94
citations
affunlabeled
Vehicular Networks for a Greener Environment: A Survey
Maazen Alsabaan, Waleed Alasmary, Abdurhman Albasir, Kshirasagar Naik
2012· article· en· IEEE Communications Surveys & Tutorials· Engineering
machine prediction:candidate · noneconsensus · none
92
citations
affunlabeled
A Survey on Trust Models in Heterogeneous Networks
Jie Wang, Zheng Yan, Haiguang Wang, Tieyan Li, Witold Pedrycz
2022· article· en· IEEE Communications Surveys & Tutorials· Social Sciences
machine prediction:candidate · noneconsensus · none
85
citations

How this was built: Screen · Findings · About