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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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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
Evidence
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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 36 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.

affno abstractunlabeled
IEEE Transactions on Information Theory publication information
Emina Soljanin, Stark C. Draper, Aaron B. Wagner, Alexander Barg, Hans‐Andrea Loeliger, Tom Richardson +68 more
2019· article· en· IEEE Transactions on Information Theory· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
IEEE Transactions on Information Theory publication information
Elza Erkip, Stark C. Draper, Daniela Tuninetti, Prakash Narayan, Alexander Barg, Hans‐Andrea Loeliger +62 more
2018· article· en· IEEE Transactions on Information Theory· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affno abstractunlabeled
IEEE Transactions on Information Theory publication information
Christina Fragouli, Parastoo Sadeghi, Edmund Yeh, Muriel Édard, P. Praveen Kumar, Matthieu R. Bloch +8 more
2024· article· en· IEEE Transactions on Information Theory· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affno abstractunlabeled
IEEE Transactions on Information Theory publication information
Emina Soljanin, Stark C. Draper, Aaron B. Wagner, Alexander Barg, Hans‐Andrea Loeliger, Tom Richardson +67 more
2019· article· en· IEEE Transactions on Information Theory· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affunlabeled
wi20cnd.rtl
2021· dataset· en· Geological Survey of Denmark and Greenland (GEUS)· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
fundno affunlabeled
Spectrally Transformed Kernel Regression
Runtian Zhai, Rattana Pukdee, Roger Jin, Maria-Florina Balcan, Pradeep Ravikumar
2024· preprint· en· arXiv (Cornell University)· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Using Triple Point Alone to Predict Saturation Line
Huan Guo, Haoyu Wang, Yi Zhang, Yujie Xu, zhiwei Ge, Hai‐Sheng Chen
2024· preprint· en· SSRN Electronic Journal· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
CODING DATA
Matthew Nelder
2019· dataset· en· Figshare· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
aboutno affunlabeled
PAR
2008· article· en· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
aboutno affunlabeled
Around the World in Eight Hundred Days
2011· other· en· AUSpace (Athabasca University)· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Basics of SVM Method and Least Squares SVM
Kourosh Parand, Fatemeh Baharifard, Alireza Afzal Aghaei, M. Jani
2023· book-chapter· en· Industrial and applied mathematics· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
fundno affunlabeled
Perspectives on Stochastic Localization
Bobby Shi, Kevin Tian, Matthew S. Zhang
2025· preprint· en· ArXiv.org· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
fundno affno abstractunlabeled
Machine Learning and Soft Computing
2025· book· en· Communications in computer and information science· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Relative Monte Carlo for Reinforcement Learning
A. Bazerghi, Sébastien Martin, Garrett van Ryzin
2024· preprint· en· SSRN Electronic Journal· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Grid-Based DNN PCGML
Matthew Guzdial, Sam Snodgrass, Adam Summerville
2022· book-chapter· en· Synthesis lectures on games and computational intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
YASIN DATA for analysis mk.xlsx
Yasin Yasin
2022· dataset· en· Figshare· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
affno abstractunlabeled
Statistical Profiling of Hybrid CNN-SVM Effectiveness
Abdallah Benkadja, Alaidine Ben Ayed, Ismaïl Biskri, Nadia Ghazzali
2024· book-chapter· en· Studies in classification, data analysis, and knowledge organization· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations

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