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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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Image and Signal Denoising Methods
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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.

1,335 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.
1,335 works in the cohort · of 4,299,418page 5 of 27

Labels cover 0 of 1,335 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 1,335 of 1,335 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
Errors-in-variables estimation with wavelets
Ramazan Gençay, Nikola Gradojević
2011· article· en· Journal of Statistical Computation and Simulation· Computer Science
machine prediction:candidate · noneconsensus · none
28
citations
affunlabeled
Noise Invalidation Denoising
Soosan Beheshti, SayedMasoud Hashemi, Xiao–Ping Zhang, Nima Nikvand
2010· article· en· IEEE Transactions on Signal Processing· Computer Science
machine prediction:candidate · noneconsensus · none
28
citations
fundno affunlabeled
Ultrasonic signal denoising based on autoencoder
Fei Gao, Bing Li, Lei Chen, Xiang Wei, Zhongyu Shang, Chen He
2020· article· en· Review of Scientific Instruments· Computer Science
machine prediction:candidate · noneconsensus · none
28
citations
affno abstractunlabeled
Wavelets from the Loop Scheme
Bin Han, Zuowei Shen
2005· article· en· Journal of Fourier Analysis and Applications· Computer Science
machine prediction:candidate · noneconsensus · none
27
citations
affunlabeled
Color image denoising using evolutionary computation
Rastislav Lukàč, Konstantinos N. Plataniotis, A.N. Venetsanopoulos
2005· article· en· International Journal of Imaging Systems and Technology· Computer Science
machine prediction:candidate · noneconsensus · none
26
citations
affunlabeled
Fractal-wavelet image denoising
Mohsen Ghazel, G.H. Freeman, Edward R. Vrscay
2003· article· en· Proceedings - International Conference on Image Processing· Computer Science
machine prediction:candidate · noneconsensus · none
24
citations
affno abstractunlabeled
Wavelets with Crystal Symmetry Shifts
Joshua D. MacArthur, Keith F. Taylor
2011· article· en· Journal of Fourier Analysis and Applications· Computer Science
machine prediction:candidate · noneconsensus · none
23
citations

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