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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
fundfunder
venuejournal
aboutaboutness

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 43 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
Thermal information processing using phase change materials
Swayam Sahoo, Anne Lamirand, Infante Ingrid C., Victor Pierron, Laurence Méchin, Luc G. Fréchette +1 more
2023· preprint· en· HAL (Le Centre pour la Communication Scientifique Directe)· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
fundno affunlabeled
Operator Learning Renormalization Group
Xiu-Zhe Luo, Di Luo, Roger G. Melko
2024· preprint· en· arXiv (Cornell University)· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
venueno affunlabeled
A Softcomputing Knowledge Areas Model
Labib Arafeh, Bashar Mufid
2015· article· en· Journal of Advances in Management Sciences & Information Systems· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Image Processing With Artificial Neural Nets
P. Bellehumeur, Guerrón Torres, P.J. Lagacé, F.G. Mandoles, D. Mukhedkar
2005· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Directional Clustering
2005· other· en· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Three-Phase Circuits
D. Sundararajan
2019· book-chapter· en· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Feedback: Sorting Signal from Noise
Heather Grace von Stackelberg, Sarah Barbour
2013· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Specia li ssue on Advances i nW eb Intelligence
Stefan Runde, Vijay V. Raghavan, Irwin King, Jimmy Xiangji Huang
2012· article· en· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affunlabeled
Complex Self-reproducing Systems
Roderick Edwards, Aude Maignan
2013· preprint· en· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Data Fitting
Sun-Chong Wang
2003· book-chapter· en· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Advanced Topics in Random Processes
Serguei Primak, Valeri Kontorovich, V. Lyandres
2004· other· en· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations

How this was built: Screen · Findings · About