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
Parallel Computing and Optimization 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.

2,094 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.
2,094 works in the cohort · of 4,299,418page 21 of 42

Labels cover 1 of 2,094 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 2,094 of 2,094 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
A design space analysis of Java processors
M. Watheq El‐Kharashi, J. Pfrimmer, K.F. Li, Fayez Gebali
2004· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
4
citations
affunlabeled
Peruse and Profit
Snehasish Kumar, Vijayalakshmi Srinivasan, Amirali Sharifian, William N. Sumner, Arrvindh Shriraman
2016· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
4
citations
affunlabeled
EASE
Nathan Skillen, Viswanathan Manickam, Alex Aravind
2011· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
4
citations
affunlabeled
ComP-net
Michael LeBeane, Khaled Hamidouche, Brad Benton, Maurício Breternitz, Steven K. Reinhardt, Lizy K. John
2018· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
4
citations
affunlabeled
Challenges of Memory Management on Modern NUMA System
Fabien Gaud, Baptiste Lepers, Justin Funston, Mohammad Dashti, Alexandra Fedorova, Vivien Quéma +2 more
2015· article· en· Queue· Computer Science
machine prediction:candidate · noneconsensus · none
4
citations
affunlabeled
Preparing the TAU performance system for exascale and beyond
Kevin Huck, Sameer Shende, Allen D. Malony, Camille Coti, Wyatt Spear, Jordi Alcaraz +8 more
2025· article· en· The International Journal of High Performance Computing Applications· Computer Science
machine prediction:candidate · noneconsensus · none
4
citations
affno abstractunlabeled
Parallel Ant Brood Graph Partitioning in Julia
Jose J. Mijares Chan, Yuyin Mao, Parimala Thulasiraman, Ruppa K. Thulasiram
2016· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
4
citations
affunlabeled
Automated Generation of Custom Processor Core from C Code
Jelena Trajković, Samar Abdi, Gabriela Nicolescu, Daniel D. Gajski
2012· article· en· Journal of Electrical and Computer Engineering· Computer Science
machine prediction:candidate · noneconsensus · none
3
citations

How this was built: Screen · Findings · About