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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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Sparse and Compressive Sensing Techniques
Retraction
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Study design
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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.

892 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.
892 works in the cohort · of 4,299,418page 1 of 18

Labels cover 1 of 892 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 892 of 892 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
Quantum State Tomography via Compressed Sensing
David Groß, Yi-Kai Liu, Steven T. Flammia, Stephen Becker, Jens Eisert
2010· article· en· Physical Review Letters· Engineering
machine prediction:candidate · noneconsensus · none
1,124
citations
affunlabeled
The Kernel Recursive Least-Squares Algorithm
Yaakov Engel, Shie Mannor, Ron Meir
2004· article· en· IEEE Transactions on Signal Processing· Engineering
machine prediction:candidate · noneconsensus · none
1,096
citations
affno abstractunlabeled
Kernel Matching Pursuit
Pascal Vincent, Yoshua Bengio
2002· article· en· Machine Learning· Engineering
machine prediction:candidate · noneconsensus · none
322
citations
fundno affunlabeled
[no title]
Mark Rudelson, Roman Vershynin
2005· article· en· International Mathematics Research Notices· Engineering
machine prediction:candidate · insufficient_payloadconsensus · none
170
citations
fundno affunlabeled
Dual-coded compressive hyperspectral imaging
Xing Lin, Gordon Wetzstein, Yebin Liu, Qionghai Dai
2014· article· en· Optics Letters· Engineering
machine prediction:candidate · noneconsensus · none
150
citations
affunlabeled
Convex Neural Networks
Yoshua Bengio, Nicolas Le Roux, Pascal Vincent, Olivier Delalleau, Patrice Marcotte
2005· article· en· Engineering
machine prediction:candidate · noneconsensus · none
138
citations
affunlabeled
Convex Multi-view Subspace Learning
Martha White, Xinhua Zhang, Dale Schuurmans, Yaoliang Yu
2012· article· en· Engineering
machine prediction:candidate · noneconsensus · none
128
citations
fundno affunlabeled
CaSCADE: Compressed Carrier and DOA Estimation
Shahar Stein Ioushua, Or Yair, Déborah Cohen, Yonina C. Eldar
2017· article· en· IEEE Transactions on Signal Processing· Engineering
machine prediction:candidate · noneconsensus · none
123
citations
affno abstractunlabeled
Euclidean Distance Matrices and Applications
Nathan Krislock, Henry Wolkowicz
2011· book-chapter· en· International series in management science/operations research/International series in operations research & management science· Engineering
machine prediction:candidate · noneconsensus · none
110
citations
affunlabeled
Exact Regularization of Convex Programs
Michael P. Friedlander, Paul Tseng
2007· article· en· SIAM Journal on Optimization· Engineering
machine prediction:candidate · noneconsensus · none
105
citations
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