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
Distributed and Parallel Computing Systems
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.

2,076 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.
2,076 works in the cohort · of 4,299,418page 1 of 42

Labels cover 5 of 2,076 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 2,076 of 2,076 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.

fundno affno abstractunlabeled
The Journal of Supercomputing
2013· paratext· en· The Journal of Supercomputing· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · none
276
citations
afffundunlabeled
DEAP
François-Michel De Rainville, Félix-Antoine Fortin, Marc-André Gardner, Marc Parizeau, Christian Gagné
2012· article· en· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · none
189
citations
affunlabeled
Rucio: Scientific Data Management
2019· article· en· Computing and Software for Big Science· Computer Science
machine prediction:candidate · noneconsensus · none
179
citations
afffundaboutunlabeled
Deploying a Top-100 Supercomputer for Large Parallel Workloads
Marcelo Ponce, Ramses van Zon, Scott Northrup, Daniel Gruner, Joseph S. Chen, Fatih Ertinaz +11 more
2019· preprint· en· Proceedings of the Practice and Experience in Advanced Research Computing on Rise of the Machines (learning)· Computer Science
machine prediction:candidate · noneconsensus · none
171
citations
fundno affno abstractunlabeled
Perspectives on grid computing
Uwe Schwiegelshohn, Rosa M. Badía, Marian Bubak, Marco Danelutto, Schahram Dustdar, Fabrizio Gagliardi +15 more
2010· article· en· Future Generation Computer Systems· Computer Science
machine prediction:candidate · noneconsensus · none
87
citations
affunlabeled
More testing should be taught
Terry Shepard, Margaret Lamb, Diane Kelly
2001· article· en· Communications of the ACM· Computer Science
machine prediction:candidate · noneconsensus · none
86
citations
affunlabeled
ATLAS computing: Technical Design Report
T. P. A. Åkesson, P. Eerola, V. Hedberg, G. Jarlskog, B.G. Lundberg, U. Mjörnmark +2 more
2005· article· en· Lund University Publications (Lund University)· Computer Science
machine prediction:candidate · noneconsensus · none
76
citations
affno abstractunlabeled
Replica selection strategies in data grid
Rashedur M. Rahman, Reda Alhajj, Ken Barker
2008· article· en· Journal of Parallel and Distributed Computing· Computer Science
machine prediction:candidate · noneconsensus · none
56
citations
affunlabeled
Interactive resource-intensive applications made easy
H. Andrés Lagar-Cavilla, Niraj H. Tolia, Eyal de Lara, Mahadev Satyanarayanan, David R. O’Hallaron
2007· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
52
citations
affno abstractunlabeled
Dynamic Virtual Clustering with Xen and Moab
Wesley Emeneker, Dave Jackson, Joshua Butikofer, Dan Stanzione
2006· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
52
citations
affno abstractunlabeled
Replica Placement Strategies in Data Grid
Rashedur M. Rahman, Ken Barker, Reda Alhajj
2007· article· en· Journal of Grid Computing· Computer Science
machine prediction:candidate · noneconsensus · none
47
citations
fundno affgemma · no categorygpt · no categorymodels agree
Efficient local search far DAG scheduling
Min‐You Wu, Wei Shu, Jun Gu
2001· article· en· IEEE Transactions on Parallel and Distributed Systems· Computer Science
machine prediction:candidate · noneconsensus · none
46
citations
affno abstractunlabeled
Common Object Request Broker Architecture
2009· book-chapter· en· Encyclopedia of Database Systems· Computer Science
machine prediction:candidate · noneconsensus · none
42
citations
affvenueunlabeled
Datacubes: A Discrete Global Grid Systems Perspective
Matthew B.J. Purss, Perry Peterson, Peter Strobl, Clinton Dow, Zoheir Sabeur, Robert Gibb +1 more
2019· article· en· Cartographica The International Journal for Geographic Information and Geovisualization· Computer Science
machine prediction:candidate · noneconsensus · none
42
citations
fundno affno abstractunlabeled
NWChem: Exploiting parallelism in molecular simulations
Tjerk P. Straatsma, Marios Philippopoulos, J. Andrew McCammon
2000· article· en· Computer Physics Communications· Computer Science
machine prediction:candidate · noneconsensus · none
40
citations

How this was built: Screen · Findings · About