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
Lecture notes in computer science
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.

11,332 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.
11,332 works in the cohort · of 4,299,418page 67 of 227

Labels cover 8 of 11,332 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 11,332 of 11,332 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.

affno abstractunlabeled
Improvements to AdaBoost Dynamic
Érico N. de Souza, Stan Matwin
2012· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
10
citations
afffundno abstractunlabeled
Finding Environment Guarantees
Marsha Chećhik, Mihaela Gheorghiu, Arie Gurfinkel
2007· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
10
citations
affno abstractunlabeled
Continual Learning with Dual Regularizations
Xuejun Han, Yuhong Guo
2021· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
10
citations
affno abstractunlabeled
Subset-Optimized BLS Multi-signature with Key Aggregation
Foteini Baldimtsi, Konstantinos Kryptos Chalkias, François Garillot, Jonas Lindstrøm, Ben Riva, A. Roy +4 more
2025· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
10
citations
affno abstractunlabeled
Evolving Buffer Overflow Attacks with Detector Feedback
H. Güneş Kayacık, Malcolm I. Heywood, A. Nur Zincir‐Heywood
2007· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
10
citations
affno abstractunlabeled
Mining Web Logs to Improve Web Caching and Prefetching
Qiang Yang, Henry Haining Zhang, Ian Tian Yi Li, Ye Lü
2001· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
10
citations
affno abstractunlabeled
Dynamic Shannon Coding
Travis Gagie
2004· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
10
citations
affno abstractunlabeled
Timing Tolerances in Safety-Critical Software
Alan Wassyng, Mark Lawford, Xiayong Hu
2005· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
10
citations
affno abstractunlabeled
An Addition Strategy for Reduct Construction
Cong Gao, Yiyu Yao
2014· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
10
citations
affno abstractunlabeled
Multiplexing of Partially Ordered Events
Colin Campbell, Margus Veanes, Jiale Huo, Alexandre Petrenko
2005· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
10
citations
affno abstractunlabeled
Foundations and Practice of Security
Gabriela Nicolescu, Assia Tria, José M. Fernandez, Jean-Yves Marion, Joaquín García-Alfaro
2021· book· en· Lecture notes in computer science· Social Sciences
machine prediction:candidate · noneconsensus · none
10
citations
affno abstractunlabeled
Region-Based Image Retrieval Using Multiple-Features
Veena Sridhar, Mário A. Nascimento, Xiaobo Li
2002· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
10
citations
affno abstractunlabeled
Fairness and Aggregation: A Primal Decomposition Study
A. Girard, Catherine Rosenberg, Mohammed Khemiri
2000· book-chapter· en· Lecture notes in computer science· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
10
citations

How this was built: Screen · Findings · About