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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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Face and Expression Recognition
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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.

895 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.
895 works in the cohort · of 4,299,418page 6 of 18

Labels cover 0 of 895 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 895 of 895 works in this cohort. Predictions are machine_predicted_unvalidated teacher distillation outputs. Candidate is the union; consensus is the intersection.

affno abstractunlabeled
Spectral Metric Learning
Benyamin Ghojogh, Mark Crowley, Fakhri Karray, Ali Ghodsi
2022· book-chapter· en· Computer Science
distilled prediction:candidate · insufficient_payloadconsensus · insufficient_payload
13
citations
afffundno abstractunlabeled
Facial pose from 3D data
Ajit Rajwade, Martin D. Levine
2006· article· en· Image and Vision Computing· Computer Science
distilled prediction:candidate · noneconsensus · none
13
citations
affunlabeled
Adaptive asymmetrical SVM and genetic algorithms based iris recognition
Kaushik Roy, Prabir Bhattacharya
2008· article· en· Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition· Computer Science
distilled prediction:candidate · metaepi_narrow+scholarly_communication+insufficient_payloadconsensus · metaepi_narrow+insufficient_payload
12
citations
affunlabeled
Algorithms of fast SVM evaluation based on subspace projection
Jianxiong Dong, Ching Y. Suen, Adam Krzyżak
2006· article· en· Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005.· Computer Science
distilled prediction:candidate · metaepi_narrowconsensus · none
12
citations
fundno affunlabeled
OPTIMAL SUBSPACE ANALYSIS FOR FACE RECOGNITION
Haitao Zhao, Pong C. Yuen, Jingyu Yang
2005· article· en· International Journal of Pattern Recognition and Artificial Intelligence· Computer Science
distilled prediction:candidate · noneconsensus · none
12
citations
affunlabeled
Multitask Metric Learning: Theory and Algorithm
Boyu Wang, Hejia Zhang, Peng Liu, Zebang Shen, Joëlle Pineau
2019· article· en· International Conference on Artificial Intelligence and Statistics· Computer Science
distilled prediction:candidate · noneconsensus · none
11
citations
aboutno affunlabeled
A New Hybrid Feature Selection Method Using T-test and Fitness Function
Husam Ali Abdulmohsin, Hala Bahjat Abdul Wahab, Abdul Mohssen Jaber Abdul Hossen
2021· article· en· Computers, materials & continua/Computers, materials & continua (Print)· Computer Science
distilled prediction:candidate · metaepi_narrow+scholarly_communicationconsensus · metaepi_narrow
11
citations
affaboutunlabeled
Infrared face recognition using texture descriptors
Moulay A. Akhloufi, Abdelhakim Bendada
2010· article· en· Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE· Computer Science
distilled prediction:candidate · noneconsensus · none
10
citations
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