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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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Manufacturing Process and Optimization
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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.

1,522 results · 1 filter active ·
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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.
1,522 works in the cohort · of 4,299,418page 10 of 31

Labels cover 0 of 1,522 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 1,522 of 1,522 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.

afffundno abstractunlabeled
Improving Design Productivity and Product Data Consistency
Fanny Giguère, Louis Rivest, Alain Desrochers
2003· book-chapter· en· IFIP advances in information and communication technology· Engineering
machine prediction:candidate · noneconsensus · none
5
citations
affno abstractunlabeled
Set-Based Prototyping with Digital Mock-Up Technologies
Boris Toche, Robert Pellerin, Clément Fortin, Greg Huet
2012· book-chapter· en· IFIP International Federation for Information Processing/IFIP· Engineering
machine prediction:candidate · noneconsensus · none
5
citations
affunlabeled
Capturing and analysing how designers use CAD software
Samira Sadeghi, Thomas Dargon, Louis Rivest, Jean-Philippe Pernot
2016· preprint· en· SAM, the Arts et Métiers ParisTech open access repository (Paris Institute of Technology)· Engineering
machine prediction:candidate · noneconsensus · none
5
citations
affno abstractunlabeled
Design for manufacturing applied to turbomachine components
Julien Chaves‐Jacob, Gérard Poulachon, Emmanuel Duc, Christian Geffroy
2011· article· en· The International Journal of Advanced Manufacturing Technology· Engineering
machine prediction:candidate · noneconsensus · none
5
citations
venueno affno abstractunlabeled
Determining Optimal Design Specification in the House of Quality
Dian Retno Sari Dewi, Dini Endah Setyo Rahaju, Maureen Angela, Irene Karijadi, Luh Juni Asrini
2024· article· en· Mathematical Modelling and Engineering Problems· Engineering
machine prediction:candidate · noneconsensus · none
5
citations
affno abstractunlabeled
Proceedings of Graphics Interface 2014
Paul G. Kry, Andrea Bunt
2014· article· en· Graphics Interface· Engineering
machine prediction:candidate · noneconsensus · none
5
citations
affunlabeled
Selected Disassembly Planning for Product Maintainability
Qingjin Peng, Chulho Chung
2007· article· en· Volume 4: ASME/IEEE International Conference on Mechatronic and Embedded Systems and Applications and the 19th Reliability, Stress Analysis, and Failure Prevention Conference· Engineering
machine prediction:candidate · noneconsensus · none
4
citations
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