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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 Vision Computing
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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.

55 results · 1 filter active ·
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20012025
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Machine labels · sparse coverage
Evidence
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Citations
An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
55 works in the cohort · of 4,299,418page 1 of 2

Labels cover 0 of 55 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 55 of 55 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.

affno abstractunlabeled
Semiautomatic segmentation with compact shape prior
Piali Das, Olga Veksler, Vyacheslav Zavadsky, Yuri Boykov
2008· article· en· Image and Vision Computing· Computer Science
machine prediction:candidate · noneconsensus · none
81
citations
affno abstractunlabeled
Shape retrieval with eigen-CSS search
Mark S. Drew, Tim K. Lee, Andrew Rova
2008· article· en· Image and Vision Computing· Computer Science
machine prediction:candidate · noneconsensus · none
22
citations
affno abstractunlabeled
3D surface modeling from curves
D. Tubic, P. Hébert, Denis Laurendeau
2004· article· en· Image and Vision Computing· Engineering
machine prediction:candidate · noneconsensus · none
16
citations
afffundno abstractunlabeled
Facial pose from 3D data
Ajit Rajwade, Martin D. Levine
2006· article· en· Image and Vision Computing· Computer Science
machine prediction:candidate · noneconsensus · none
13
citations
affno abstractunlabeled
Non-local adaptive structure tensors
Vincent Doré, Reza Farrahi Moghaddam, Mohamed Cheriet
2011· article· en· Image and Vision Computing· Computer Science
machine prediction:candidate · noneconsensus · none
11
citations
affno abstractunlabeled
View matching with blob features
Per-Erik Forssén
2006· article· en· Image and Vision Computing· Computer Science
machine prediction:candidate · noneconsensus · none
8
citations
affno abstractunlabeled
Shape based appearance model for kernel tracking
Zhijie Wang, Mohamed Ben Salah, Hong Zhang, Nilanjan Ray
2012· article· en· Image and Vision Computing· Computer Science
machine prediction:candidate · noneconsensus · none
7
citations
afffundno abstractunlabeled
Photo Hull regularized stereo
Shufei Fan, Frank P. Ferrie
2008· article· en· Image and Vision Computing· Computer Science
machine prediction:candidate · noneconsensus · none
6
citations
affno abstractunlabeled
Self-supervised part segmentation via motion imitation
Yanping Zhang, Qiaokang Liang, Kunlin Zou, Zhengwei Li, Wei Sun, Yaonan Wang
2022· article· en· Image and Vision Computing· Computer Science
machine prediction:candidate · noneconsensus · none
5
citations
afffundno abstractunlabeled
Novel depth cues from light scattering
Danielle L. Levesque, F. Deschênes
2006· article· en· Image and Vision Computing· Computer Science
machine prediction:candidate · noneconsensus · none
3
citations
affno abstractunlabeled
3D surface modeling from curves
D TUBI
2004· article· en· Image and Vision Computing· Engineering
machine prediction:candidate · noneconsensus · none
1
citations

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