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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.

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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 21 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. 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
Call for papers
Jinsong Wu, Igor Bisio, Haibo Li, Ekram Hossain, Chris Gniady, Massimo Valla
2013· paratext· en· IEEE Transactions on Communications· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
aboutno affunlabeled
EFRAILTY.ORG: ANALYSIS OF INITIAL USERS
Megan Cheslock, Stephanie Denise M. Sison, Lily Zhong, Natalie Newmeyer, Kuan-Yuan Wang, Andrea Wershof Schwartz +2 more
2024· article· en· Innovation in Aging· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Trouble Sleeping?
Allison Harding, Katie Eng, Manal Rana, Isaiah Martinez
2024· article· en· Aging and (Geron) Technology· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Classification of Elderly’s Home Activities using Tree-Based Model
Pei Pei Chiew, Xin Rhu Lim, Chew Peng Gan, Yi-Fei Tan, Siew Khew Koh, Mahboobeh Zangeneh Sirdari
2024· article· en· Journal of Advanced Research in Applied Sciences and Engineering Technology· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Activity tracking
Halimat Alabi, Yvonne Coady
2014· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Table of contents
Wei‐Tek Tsai, Wenjun Wu, Michael Standards, Yong Cui, Qi Sun, Ke Xu +27 more
2014· article· en· IEEE Internet Computing· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
affunlabeled
DeepKøver
Mehdi Najjar, François Courtemanche, Habib Hamam, Alexandre Dion, Jérémy Bauchet, André Mayers
2013· book-chapter· en· IGI Global eBooks· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations

How this was built: Screen · Findings · About