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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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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.

2,769 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.
2,769 works in the cohort · of 4,299,418page 3 of 56

Labels cover 6 of 2,769 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 2,769 of 2,769 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
Correlational Neural Networks
Sarath Chandar, Mitesh M. Khapra, Hugo Larochelle, Balaraman Ravindran
2015· article· en· Neural Computation· Computer Science
machine prediction:candidate · noneconsensus · none
137
citations
affno abstractunlabeled
Neural Probabilistic Language Models
Yoshua Bengio, Holger Schwenk, Jean-Sébastien Senécal, Fréderic Morin, Jean‐Luc Gauvain
2006· book-chapter· en· Studies in fuzziness and soft computing· Computer Science
machine prediction:candidate · noneconsensus · none
132
citations
affunlabeled
Deep Learning for NLP (without Magic)
Richard Socher, Christopher D. Manning
2012· article· en· Meeting of the Association for Computational Linguistics· Computer Science
machine prediction:candidate · noneconsensus · none
132
citations
affunlabeled
A Survey of Data Augmentation Approaches for NLP
Steven Y. Feng, Varun Gangal, Jason Wei, Sarath Chandar, Soroush Vosoughi, Teruko Mitamura +1 more
2021· preprint· en· Computer Science
machine prediction:candidate · noneconsensus · none
129
citations
afffundunlabeled
Reinforced Multi-Teacher Selection for Knowledge Distillation
Fei Yuan, Linjun Shou, Jian Pei, Wutao Lin, Ming Gong, Yan Fu +1 more
2021· article· en· Proceedings of the AAAI Conference on Artificial Intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
121
citations
affno abstractunlabeled
Dsharp: Fast d-DNNF Compilation with sharpSAT
Christian Muise, Sheila A. McIlraith, J. Christopher Beck, Eric Hsu
2012· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
108
citations
affno abstractunlabeled
Evaluation of Retrieval-Augmented Generation: A Survey
Hao Yu, Aoran Gan, Kai Zhang, Shiwei Tong, Qi Liu, Zhaofeng Liu
2025· book-chapter· en· Communications in computer and information science· Computer Science
machine prediction:candidate · noneconsensus · none
104
citations
affunlabeled
Order-Planning Neural Text Generation From Structured Data
Lei Sha, Lili Mou, Tianyu Liu, Pascal Poupart, Sujian Li, Baobao Chang +1 more
2018· article· en· Proceedings of the AAAI Conference on Artificial Intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
101
citations
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