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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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Context-Aware Activity Recognition Systems
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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
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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.

1,215 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.
1,215 works in the cohort · of 4,299,418page 11 of 25

Labels cover 1 of 1,215 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 1,215 of 1,215 works in this cohort. Predictions are machine_predicted_unvalidated teacher distillation outputs. Candidate is the union; consensus is the intersection.

affunlabeled
Energy Optimization for Outdoor Activity Recognition
Mehdi Boukhechba, Abdenour Bouzouane, Bruno Bouchard, Robert J. Vallerand, Sylvain Giroux
2016· article· en· Journal of Sensors· Computer Science
distilled prediction:candidate · noneconsensus · none
6
citations
affno abstractunlabeled
A Scalable Testing Framework for Location-Based Services
Yu Jiang, Andrew F. Tappenden, James Miller, Michael R. Smith
2009· article· en· Journal of Computer Science and Technology· Computer Science
distilled prediction:candidate · noneconsensus · none
6
citations
affunlabeled
Getting mobile with mobile devices
Darren Minifie, Yvonne Coady
2009· article· en· Computer Science
distilled prediction:candidate · noneconsensus · none
6
citations
affunlabeled
Context-Aware Mobile Learning on the Semantic Web
Rachid Benlamri, Jawad Berri, Yacine Atif
2008· book-chapter· en· IGI Global eBooks· Computer Science
distilled prediction:candidate · metaepi_narrow+insufficient_payloadconsensus · none
6
citations
affunlabeled
WaterHCI: Water in Human-Computer Interaction
Maria Montoya Vega, Ian Smith, Christal Clashing, Rakesh Patibanda, Swamy Ananthanarayan, Sarah Jane Pell +1 more
2024· article· en· Foundations and Trends® in Human–Computer Interaction· Computer Science
distilled prediction:candidate · metaepi_narrow+scholarly_communicationconsensus · none
6
citations
afffundunlabeled
A Classification Framework for Context-aware Mobile Learning Systems
Richard A. W. Tortorella, Kinshuk Kinshuk, Nian‐Shing Chen, Sabine Graf
2017· article· en· International Journal of Modern Education and Computer Science· Computer Science
distilled prediction:candidate · scholarly_communicationconsensus · none
6
citations
affno abstractunlabeled
Uncertain inference control in privacy protection
Xiangdong An, Dawn Jutla, Nick Cercone, Charnyote Pluempitiwiriyawej, Hai Wang
2009· article· en· International Journal of Information Security· Computer Science
distilled prediction:candidate · noneconsensus · none
5
citations
affunlabeled
State-of-the-Art Assistive Technology for People with Dementia
Clifton Phua, Patrice Roy, Hamdi Aloulou, Jit Biswas, Andrei Tolstikov, Victor Siang-Fook Foo +5 more
2011· book-chapter· en· Advances in computational intelligence and robotics book series· Computer Science
distilled prediction:candidate · noneconsensus · none
5
citations

How this was built: Screen · Findings · About