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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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Advanced Research in Systems and Signal Processing
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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
aboutaboutness

The four routes compose: require the funder route and exclude affiliation to get the funder-only stratum no affiliation-based frame ever sees.

103 results · 1 filter active ·
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20002025
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Machine labels · sparse coverage
Evidence
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An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
103 works in the cohort · of 4,299,418page 2 of 3

Labels cover 0 of 103 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 103 of 103 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
The MAS-AI model: Model of ASsement of Artificial Intelligence.
Iben Fasterholdt, Kristian Kidholm, Anne Gerdes, Malene Grubbe Hildebrandt, Astrid Barkler, Valeria E. Rac +4 more
2023· article· en· University of Southern Denmark Research Portal (University of Southern Denmark)· Engineering
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Appendix F: List of ORC Test Systems
Ali R. Al-Roomi
2021· other· en· Engineering
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
aboutno affunlabeled
Построение модели оценки потенциала инновационного проекта и ее оценки на основе гибридных экспертных систем
Пятковский Олег Иванович, Габова Мария Андреевна
2013· article· en· Известия Алтайского государственного университета· Engineering
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Guest Editorial Special Issue on ISCAS 2010
Maged Ghoneima, Yong Lian, Gabriele Manganaro, Shahriar Mirabbasi, Christian Piguet, Wouter A. Serdijn
2011· editorial· en· IEEE Transactions on Circuits and Systems I Regular Papers· Engineering
machine prediction:candidate · noneconsensus · none
0
citations
venueaboutno affno abstractunlabeled
IEEE Canada Regional Committee Members - 2002
2003· article· en· Canadian Journal of Electrical and Computer Engineering· Engineering
machine prediction:candidate · noneconsensus · none
0
citations
venueno affno abstractunlabeled
10.51847/8mGVsMZtRw
2000· article· en· Time to knit· Engineering
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
afffundunlabeled
A Method of Finding Representative Sets of Rules
Jiye Li, Nick Cercone, Jianchao Han
2007· article· en· 2007 IEEE International Conference on Granular Computing (GRC 2007)· Engineering
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Issue Information
Mike J. Grimble, Roméo Ortega, Kalle Åström, Robert R. Bitmead, Guy A. Dumont, Robert L. Kosut +11 more
2023· paratext· en· International Journal of Adaptive Control and Signal Processing· Engineering
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations

How this was built: Screen · Findings · About