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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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Digital Transformation in Industry
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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.

948 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.
948 works in the cohort · of 4,299,418page 3 of 19

Labels cover 6 of 948 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 948 of 948 works in this cohort. Predictions are machine_predicted_unvalidated teacher distillation outputs. Candidate is the union; consensus is the intersection.

afffundno abstractunlabeled
A framework for identifying and analysing industry 4.0 scenarios
William de Paula Ferreira, Fabiano Armellini, Luis Antonio de Santa-Eulália, Vincent Thomasset-Laperrière
2022· article· en· Journal of Manufacturing Systems· Engineering
distilled prediction:candidate · noneconsensus · none
38
citations
affunlabeled
Sustainable Manufacturing in Industry 4.0
Hamed Gholami, Georges Abdul-Nour, Safian Sharif, Dalia Štreimikienė
2023· book· en· Engineering
distilled prediction:candidate · metaepi_narrow+research_integrity+insufficient_payloadconsensus · none
38
citations
affunlabeled
Insights on mapping Industry 4.0 and Education 4.0
Sourojeet Chakraborty, Yris Gonzalez-Triana, Jorge Mendoza, Daniela Galatro
2023· article· en· Frontiers in Education· Engineering
distilled prediction:candidate · noneconsensus · none
38
citations
aboutno affunlabeled
Smart Manufacturing
Seeram Ramakrishna
2017· article· es· Procedia Manufacturing· Engineering
distilled prediction:candidate · metaepi_narrow+scholarly_communication+insufficient_payloadconsensus · none
37
citations
affunlabeled
Digital Twin for Railway: A Comprehensive Survey
Sara Ghaboura, Rahatara Ferdousi, Fedwa Laamarti, Chunsheng Yang, Abdulmotaleb El Saddik
2023· article· en· IEEE Access· Engineering
distilled prediction:candidate · noneconsensus · none
37
citations
affunlabeled
Digital twin for predictive maintenance
Zheng Liu, Erik Blasch, Min Liao, Chunsheng Yang, Kazuhiko Tsukada, Norbert Meyendorf
2023· article· en· Engineering
distilled prediction:candidate · noneconsensus · none
31
citations
afffundunlabeled
Digital twins for well-being: an overview
Rahatara Ferdousi, Fedwa Laamarti, M. Anwar Hossain, Chunsheng Yang, Abdulmotaleb El Saddik
2022· article· en· Digital Twin· Engineering
distilled prediction:candidate · noneconsensus · none
28
citations
affunlabeled
Ripples of Change – An AI Job Crafting Model for Human-in-Control
Rania Afiouni, Alain Pinsonneault
2022· article· en· Proceedings of the ... Annual Hawaii International Conference on System Sciences/Proceedings of the Annual Hawaii International Conference on System Sciences· Engineering
distilled prediction:candidate · metaepi_narrow+open_scienceconsensus · none
28
citations
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How this was built: Screen · Findings · About