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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 32 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.

aboutno affunlabeled
Extension of Naturalized Flow Using Linear Regression
John Zhu, Nelun Fernando, Carla G. Guthrie
2020· article· en· World Environmental and Water Resources Congress 2020· Computer Science
machine prediction:candidate · noneconsensus · none
1
citations
aboutno affunlabeled
Let’s deplatform the deplatformers
Salvatore Babones
2019· article· en· The Sydney eScholarship Repository (The University of Sydney)· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Memory Models: Quantitative
Bennet B. Murdock
2015· book-chapter· en· Elsevier eBooks· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
venueno affno abstractunlabeled
10.1016/s0967-0653(97)89114-4
2000· article· en· Time to knit· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
fundaboutno affunlabeled
Re-Configurable Hardware Based Fractal Neural Processor.
A. H. Abouali, Sabry M. Abdel-Moetty, B. Earl Wells
2006· article· en· Parallel and Distributed Computing Systems (ISCA)· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Noise and Signal Interaction
Rachel Kuske
2006· article· en· Computing in Science & Engineering· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
The Self-Organising Hierarchical Variance Map
M.J. Kyan, Ling Guan
2006· article· en· The 2006 IEEE International Joint Conference on Neural Network Proceedings· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Dynamic Inference with Neural Interpreters
Nasim Rahaman, Muhammad Waleed Gondal, Shruti Joshi, Peter Gehler, Yoshua Bengio, Francesco Locatello +1 more
2021· article· en· Neural Information Processing Systems· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Working with any number of hidden layers
Ahmed Fawzy Gad, Fatima Ezzahra Jarmouni
2021· book-chapter· en· Elsevier eBooks· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Tandem system based on competing information
Li-Rong Dai
2011· article· en· Journal of Tsinghua University(Science and Technology)· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Stability and KAM Theory
Kenneth R. Meyer, Glen R. Hall, Dan Offin
2008· book-chapter· en· Applied mathematical sciences· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
fundno affunlabeled
Architectural Neural Backdoors from First Principles
Harry Langford, Ilia Shumailov, Yiren Zhao, Robert Mullins, Nicolas Papernot
2024· preprint· en· arXiv (Cornell University)· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Sampling and quantization
Ha H. Nguyen, E. Shwedyk
2009· book-chapter· en· Cambridge University Press eBooks· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
venueno affunlabeled
A Novel System for Speech Recognition
Stanly Kumar Ande, K.M. Rao, Arjun Krishna
2013· article· en· Mechanical Engineering Research· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
venueno affno abstractunlabeled
Wide Diameters and Diameter of Networks.
Bo Liu, Xiankun Zhang
2008· article· en· Ars Combinatoria· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations

How this was built: Screen · Findings · About