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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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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.

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.

1,335 results · 1 filter active ·
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20002025
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Machine labels · sparse coverage
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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 3 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
Recompression of JPEG images by requantization
Heinz H. Bauschke, Chris Hamilton, Mason S. Macklem, Jonathan McMichael, N.R. Swart
2003· article· en· IEEE Transactions on Image Processing· Computer Science
machine prediction:candidate · noneconsensus · none
58
citations
afffundunlabeled
A Variational Approach to Degraded Document Enhancement
Reza Farrahi Moghaddam, Mohamed Cheriet
2009· article· en· IEEE Transactions on Pattern Analysis and Machine Intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
56
citations
affunlabeled
Curved wavelet transform for image coding
Demin Wang, Liang Zhang, A. Vincent, Filippo Speranza
2006· article· en· IEEE Transactions on Image Processing· Computer Science
machine prediction:candidate · noneconsensus · none
56
citations
affno abstractunlabeled
Multiwavelets on the Interval
Bin Han, Qingtang Jiang
2002· article· en· Applied and Computational Harmonic Analysis· Computer Science
machine prediction:candidate · noneconsensus · none
50
citations
affunlabeled
Fuzzy filters for image filtering
Hon Keung Kwan, Y. Cai
2003· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
44
citations
afffundunlabeled
CW-SSIM based image classification
Yang Gao, Abdul Rehman, Zhou Wang
2011· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
43
citations
affno abstractunlabeled
On the geodesic paths approach to color image filtering
M. Szczepański, Bogdan Smołka, Konstantinos N. Plataniotis, A.N. Venetsanopoulos
2003· article· en· Signal Processing· Computer Science
machine prediction:candidate · noneconsensus · none
42
citations
affunlabeled
Curvelet-based ground roll removal
Carson Yarham, Urs Boeniger, Felix J. Herrmann
2008· article· en· cIRcle (University of British Columbia)· Computer Science
machine prediction:candidate · noneconsensus · none
41
citations
afffundunlabeled
Adaptively Tuned Iterative Low Dose CT Image Denoising
SayedMasoud Hashemi, Narinder Paul, Soosan Beheshti, R.S.C. Cobbold
2015· article· en· Computational and Mathematical Methods in Medicine· Computer Science
machine prediction:candidate · noneconsensus · none
40
citations
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