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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.

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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.

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Computability, Logic, AI Algorithms
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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
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The four routes compose: require the funder route and exclude affiliation to get the funder-only stratum no affiliation-based frame ever sees.

805 results · 1 filter active ·
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20002025
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Machine labels · sparse coverage
Evidence
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An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
805 works in the cohort · of 4,299,418page 13 of 17

Labels cover 0 of 805 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 805 of 805 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.

afffundunlabeled
Computability of Brjuno-like functions
Michael Yampolsky, Ivan O. Shevchenko
2025· article· en· Canadian Journal of Mathematics· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Futures of Hypercomplexity
Étienne Turpin
2013· article· en· Research Online (University of Wollongong)· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Pure and Applied Mathematics
Roderick Melnik
2015· other· en· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
afffundunlabeled
Relations enumerable from positive information
Barbara F. Csima, Luke MacLean, Dino Rossegger
2025· article· en· Journal of Logic and Computation· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
The Minimum Oracle Circuit Size Problem
Eric Allender, Dhiraj Holden, Valentine Kabanets
2015· article· en· View· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Complexity and the Amending Formula
Kate Glover
2015· article· en· SSRN Electronic Journal· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Real and complex numbers
2023· book-chapter· en· Mathematical world· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
On System Algebra
Yingxu Wang
2011· book-chapter· en· IGI Global eBooks· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Channel coding
Ke-Lin Du, M. N. S. Swamy
2010· book-chapter· en· Cambridge University Press eBooks· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
fundno affunlabeled
Reverse-type Data Processing Inequality
Paula Belzig, Gao Li, Graeme Smith, Peixue Wu
2024· preprint· en· arXiv (Cornell University)· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
afffundunlabeled
Categorical Foundations of Formalized Condensed Mathematics
Dagur Tómas Ásgeirsson, Riccardo Brasca, Nikolas Kuhn, Filippo Alberto Edoardo Nuccio Mortarino Majno Di Capriglio, Adam Topaz
2024· preprint· en· arXiv (Cornell University)· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
venueno affunlabeled
When the Dean Called for Remote Programming
Robbi De Peri, Benjamin Darling
2021· article· en· Ticker The Academic Business Librarianship Review· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Modular arithmetic
2023· book-chapter· en· Mathematical world· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Feasible combinatorial matrix theory
Ariel Fernández, Michael Soltys
2013· preprint· en· arXiv (Cornell University)· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
venueno affno abstractunlabeled
A sufficient condition for Set Reconstruction.
Sridhar Ramachandran, S. Monikandan
2009· article· en· Ars Combinatoria· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Ontologies and Knowledge-Based Systems
David Poole, Alan K. Mackworth
2017· book-chapter· en· Cambridge University Press eBooks· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
manifest.xml
Michelle Cullen, David Topps
2019· dataset· en· Harvard Dataverse· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
venueno affno abstractunlabeled
10.1016/b978-0-340-67769-8.50012-4
2000· book-chapter· en· Time to knit· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
affno abstractunlabeled
AI Algorithms and Stochastic Game‐play
Karo Castro-Wunsch, William Maga, Cǎlin Anton
2015· article· en· URSCA Proceedings· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Occurrence Download
2022· dataset· en· Global Biodiversity Information Facility· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affno abstractunlabeled
Turing Machines
Tom Jenkyns, Ben Stephenson
2018· book-chapter· en· Undergraduate topics in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Computational Fun with Sturdy and Flimsy Numbers
Trevor Clokie, Thomas F. Lidbetter, Antonio J. Molina Lovett, Jeffrey Shallit, Leon Witzman
2020· article· en· DROPS (Schloss Dagstuhl – Leibniz Center for Informatics)· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
On Divisibility by 4
Rina Zazkis, Nathalie Sinclair, Peter Liljedahl
2012· book-chapter· en· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Programming
Sami Chatti, Luc Laperrière, Gunther Reinhart, Tullio Tolio
2019· book-chapter· en· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affno abstractunlabeled
The Type Ia Supernova Rate at z ≈ 0.5 from the Supernova Legacy Survey**Based on observations obtained with MegaPrime/MegaCam, a joint project of the Canada-France-Hawaii Telescope (CFHT) and CEA/DAPNIA, at CFHT, which is operated by the National Research Council (NRC) of Canada, the Institut National des Sciences de l’Univers of the Centre National de la Recherche Scientifique (CNRS) of France, and the University of Hawaii. This work is based in part on data products produced at the Canadian Astronomy Data Centre as part of the Canada-France-Hawaii Telescope Legacy Survey, a collaborative project of NRC and CNRS. This work is also based on observations obtained at the European Southern Observatory using the Very Large Telescope on the Cerro Paranal (ESO Large Program 171.A-0486), and on observations (programs GN-2004A-Q-19, GS-2004A-Q-11, GN-2003B-Q-9, and GS-2003B-Q-8) obtained at the Gemini Observatory, which is operated by the Association of Universities for Research in Astronomy, Inc., under a cooperative agreement with the National Science Foundation (NSF) on behalf of the Gemini partnership: the NSF (United States), the Particle Physics and Astronomy Research Council (United Kingdom), the National Research Council (Canada), CONICYT (Chile), the Australian Research Council (Australia), CNPq (Brazil), and CONICET (Argentina). This work is also based on observations obtained at the W. M. Keck Observatory, which is operated as a scientific partnership among the California Institute of Technology, the University of California, and the National Aeronautics and Space Administration. The Observatory was made possible by the generous financial support of the W. M. Keck Foundation.
2020· other· en· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Introduction
2011· other· en· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
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