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
Anomaly Detection Techniques and Applications
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.

1,158 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.
1,158 works in the cohort · of 4,299,418page 6 of 24

Labels cover 1 of 1,158 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 1,158 of 1,158 works in this cohort. Predictions are machine_predicted_unvalidated teacher distillation outputs. Candidate is the union; consensus is the intersection.

affno abstractunlabeled
An Evaluation Framework for Synthetic Data Generation Models
Ioannis E. Livieris, Nikos Alimpertis, George Domalis, Dimitris Tsakalidis
2024· book-chapter· en· IFIP advances in information and communication technology· Computer Science
distilled prediction:candidate · noneconsensus · none
16
citations
affno abstractunlabeled
On Diverse Asynchronous Activity Anticipation
He Zhao, Richard P. Wildes
2020· book-chapter· en· Lecture notes in computer science· Computer Science
distilled prediction:candidate · metaepi_narrowconsensus · none
16
citations
afffundunlabeled
Graph Anomaly Detection in Time Series: A Survey
Narges Armanfard
2025· article· en· IEEE Transactions on Pattern Analysis and Machine Intelligence· Computer Science
distilled prediction:candidate · noneconsensus · none
16
citations
affno abstractunlabeled
Big data fusion in Internet of Things
Zheng Yan, Jun Liu, Laurence T. Yang, Nitesh V. Chawla
2017· article· en· Information Fusion· Computer Science
distilled prediction:candidate · noneconsensus · none
15
citations
fundno affunlabeled
Data mining of resilience indicators
Ngai Hang Chan, Hoi Ying Wong
2007· article· en· IIE Transactions· Computer Science
distilled prediction:candidate · noneconsensus · none
15
citations
affno abstractunlabeled
Y-Means: An Autonomous Clustering Algorithm
Ali A. Ghorbani, Iosif-Viorel Onut
2010· book-chapter· en· Lecture notes in computer science· Computer Science
distilled prediction:candidate · metaepi_narrowconsensus · none
15
citations
affunlabeled
SiPTA
Mohammad Mehdi Zeinali Zadeh, Mahmoud Salem, Neeraj Kumar, Greta Cutulenco, Sebastian Fischmeister
2014· article· en· Computer Science
distilled prediction:candidate · noneconsensus · none
15
citations
affunlabeled
Anomaly Detection in Images
Manpreet Singh Minhas, John Zelek
2019· preprint· en· arXiv (Cornell University)· Computer Science
distilled prediction:candidate · noneconsensus · none
14
citations
affunlabeled
Statistical Anomaly Detection for Train Fleets
Anders Holst, Markus Bohlin, Jan Ekman, Ola Sellin, Björn Lindström, Stefan Larsen
2013· article· en· AI Magazine· Computer Science
distilled prediction:candidate · noneconsensus · none
14
citations
afffundunlabeled
Incremental Adversarial Learning for Polymorphic Attack Detection
Ulya Sabeel, Shahram Shah Heydari, Khalil El‐Khatib, Khalid Elgazzar
2024· article· en· IEEE Transactions on Machine Learning in Communications and Networking· Computer Science
distilled prediction:candidate · noneconsensus · none
12
citations
affunlabeled
Hidden Markov Model: Tutorial
Benyamin Ghojogh, Fakhri Karray, Mark Crowley
2019· preprint· en· Computer Science
distilled prediction:candidate · noneconsensus · none
12
citations

How this was built: Screen · Findings · About