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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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Machine Learning and Data Classification
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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.

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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.

559 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.
559 works in the cohort · of 4,299,418page 3 of 12

Labels cover 1 of 559 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 559 of 559 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
Optimal reverse prediction
Linli Xu, Martha White, Dale Schuurmans
2009· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
22
citations
afffundunlabeled
COEVOLUTION OF NEAREST NEIGHBOR CLASSIFIERS
Christian Gagné, Marc Parizeau
2007· article· en· International Journal of Pattern Recognition and Artificial Intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
21
citations
affunlabeled
Adaptive error-correcting output codes
Guoqiang Zhong, Mohamed Cheriet
2013· article· en· International Joint Conference on Artificial Intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
21
citations
affunlabeled
Meta-MapReduce for scalable data mining
Xuan Liu, Xiaoguang Wang, Stan Matwin, Nathalie Japkowicz
2015· article· en· Journal Of Big Data· Computer Science
machine prediction:candidate · noneconsensus · none
21
citations
affno abstractunlabeled
Roulette Sampling for Cost-Sensitive Learning
Victor S. Sheng, Charles X. Ling
2007· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
20
citations
affunlabeled
Ensemble Kernel Mean Matching
Yun-Qian Miao, Ahmed Farahat, Mohamed S. Kamel
2015· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
17
citations
affunlabeled
Machine learning: Supervised methods, SVM and kNN
Danilo Bzdok, Martin Krzywinski, Naomi Altman
2018· preprint· fr· HAL (Le Centre pour la Communication Scientifique Directe)· Computer Science
machine prediction:candidate · noneconsensus · none
17
citations
affunlabeled
A scalable AutoML approach based on graph neural networks
Mossad Helali, Essam Mansour, Ibrahim Abdelaziz, Julian Dolby, Kavitha Srinivas
2022· article· en· Proceedings of the VLDB Endowment· Computer Science
machine prediction:candidate · noneconsensus · none
17
citations
affunlabeled
AutoML Loss Landscapes
Yasha Pushak, Holger H. Hoos
2022· article· en· ACM Transactions on Evolutionary Learning and Optimization· Computer Science
machine prediction:candidate · noneconsensus · none
16
citations
affunlabeled
An Ensemble Model for Combating Label Noise
Yangdi Lu, Bo Yang, Wenbo He
2022· article· en· Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining· Computer Science
machine prediction:candidate · noneconsensus · none
14
citations
fundno affunlabeled
Class Adaptive Network Calibration
Bingyuan Liu, Jérôme Rony, Adrián Galdrán, José Dolz, Ismail Ben Ayed
2023· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
13
citations
affno abstractunlabeled
Forgetting Reinforced Cases
Houcine Romdhane, Luc Lamontagne
2008· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
12
citations
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