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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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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 23 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.

affno abstractunlabeled
Context Networks
Reda Alhajj, Jon Rokne
2018· book-chapter· en· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Smart Rooms
Biplab Kumer Sarker, Julian Descottes, Mohsin Sohail, Rama Krishna Kosaraju
2012· book-chapter· en· IGI Global eBooks· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Introduction
Mohammad S. Obaidat, Isaac Woungang
2011· other· en· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
aboutno affunlabeled
AVATECH: AVANET - CROWDSOURCED, REAL-TIME SNOWPACK INFORMATION
Jim Christian, Sam Whittemore, Brint Markle, Thomas A. Laakso, Andrew Sohn
2014· article· en· International Snow Science Workshop 2014 Proceedings, Banff, Canada· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Wireless Alert Technology for Elderly Care at Home
Nataša Obradović, Julie Lacerte, Véronique Provencher, Hélène Pigot, Sylvain Giroux, Hubert Kenfack Ngankam
2024· book-chapter· en· Lecture notes in networks and systems· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
A Context-Aware Healthcare Architecture for the Elderly
Tolulope Oyekanmi, Nhat Nguyen, Vangalur Alagar
2016· article· en· Lecture notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Building Context-Aware E-Commerce Systems
Anahit Martirosyan, Thomas Tran, Azzedine Boukerche
2010· book-chapter· en· IGI Global eBooks· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
WISH 2009 Preface
2009· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Novel Algorithm on Human Body Fall Detection
Kumar Saikat Halder, Ashwani Singla, Ranjit Singh
2019· book-chapter· en· Learning and analytics in intelligent systems· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
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