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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.

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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Neural Networks and Applications
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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.

2,372 results · 1 filter active ·
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20002025
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Machine labels · sparse coverage
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An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
2,372 works in the cohort · of 4,299,418page 42 of 48

Labels cover 1 of 2,372 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 2,372 of 2,372 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
Machine_Learning_to_Hardware_for_Instrumentation
Berthié Gouin-Ferland, Hamza Ezzaoui Rahali, Mohammad Mehdi Rahimifar
2023· dataset· en· Zenodo (CERN European Organization for Nuclear Research)· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
A model of memory for incidental learning
Roger A. Browse, Lisa Y. Drewell
2009· article· en· Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
FINTA/CINTA/GESTA/FIESTA Datasets
Félix Dumais, Jon Haitz Legarreta
2023· dataset· en· Zenodo (CERN European Organization for Nuclear Research)· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Manifold-Based Classifier Ensembles
Vitaliy Tayanov, Adam Krzyżak, Ching Y. Suen
2020· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
ANGELS project D.3.7. Multi-agents demonstrator
Christine Chevallereau, Mohammed-Rédha Benachenhou, Vincent Lebastard, Frédéric Boyer
2012· preprint· en· HAL (Le Centre pour la Communication Scientifique Directe)· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Computer Generated-Human Morph Stimuli
Natalie C. Bowling, Michael J. Banissy
2016· article· en· Zenodo (CERN European Organization for Nuclear Research)· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Raw Data for Statistical Analyses Cortex Submission
Amedeo D’Angiulli, Dana Wymark, Andre Telfer, Sahar Bahrami, Santina Temi
2024· dataset· en· Zenodo (CERN European Organization for Nuclear Research)· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Cascade-Correlation
Thomas R. Shultz, Scott E. Fahlman
2014· book-chapter· en· Encyclopedia of Machine Learning and Data Mining· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Neural Networks
Peter Zizler, Roberta La Haye
2024· book-chapter· en· Compact textbooks in mathematics· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Unsupervised Learning with Ferroelectric Synapses
Nikhil Garg, I. Balafrej, Yann Beilliard, D. Drouin, F. Alibart, J. Rouat
2022· preprint· en· HAL (Le Centre pour la Communication Scientifique Directe)· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Elastic Computing
2018· book-chapter· en· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Hopfield Network
B. Bass, T. Nixon
2008· book-chapter· en· Elsevier eBooks· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Efference copy and context effects.
Mark Scott, Bryan Gick
2011· article· en· The Journal of the Acoustical Society of America· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
venueno affno abstractunlabeled
Papers to Appear in ARCTIC
Karen McCullough
2010· article· en· ARCTIC· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
venueno affno abstractunlabeled
Papers to Appear in <i>ARCTIC</i>
Karen McCullough
2012· article· en· ARCTIC· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
venueno affno abstractunlabeled
10.1016/0967-0653(95)91282-9
2000· article· en· Time to knit· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
affunlabeled
Artificial Neural Networks in EEG Analysis
Markad V. Kamath, A.R.M. Upton, Jie Wu, H. S. BAJAJ, Skip Poehlman, Robert Spaziani
2011· book-chapter· en· IGI Global eBooks· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Raw Data for Statistical Analyses Cortex Submission
Amedeo D’Angiulli, Dana Wymark, Andre Telfer, Sahar Bahrami, Santina Temi
2024· dataset· en· Zenodo (CERN European Organization for Nuclear Research)· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Controlling approximation error
J DOMPIERRE, P LABBE, F GUIBAULT
2003· book-chapter· en· Elsevier eBooks· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Machine_Learning_to_Hardware_for_Instrumentation
Berthié Gouin-Ferland, Hamza Ezzaoui Rahali, Mohammad Mehdi Rahimifar
2023· dataset· en· Zenodo (CERN European Organization for Nuclear Research)· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations

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