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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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Additive Manufacturing and 3D Printing Technologies
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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.

1,448 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.
1,448 works in the cohort · of 4,299,418page 25 of 29

Labels cover 5 of 1,448 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 1,448 of 1,448 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
10.1122/1.5093033.1
Timothy J. Coogan, David O. Kazmer
2019· dataset· en· Default Digital Object Group· Engineering
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
venueno affunlabeled
Metal Powder Handling In Additive Manufacturing Application
Shu‐San Hsiau, Li-Tsung Sheng, Yi-Lun Xiao
2024· article· en· Proceedings of the ... International Conference on Fluid Flow, Heat and Mass Transfer· Engineering
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
3D Printing of Green Materials
Zohre Mousavi Nejad, Seyyed Mojtaba Mousavi, Seyyed Alireza Hashemi, Wei‐Hung Chiang, Chin Wei Lai
2022· book-chapter· en· Encyclopedia of Green Materials· Engineering
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Analyzing Additive Manufacturing Feature Spaces
Mutahar Safdar, Guy Lamouche, Padma Polash Paul, Gentry Wood, Yaoyao Fiona Zhao
2023· book-chapter· en· SpringerBriefs in applied sciences and technology· Engineering
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Introduction
Mutahar Safdar, Guy Lamouche, Padma Polash Paul, Gentry Wood, Yaoyao Fiona Zhao
2023· book-chapter· en· SpringerBriefs in applied sciences and technology· Engineering
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affno abstractunlabeled
3D printers and adverse health effects
Chun‐Yip Hon, Nikhil Rajaram, Susan M. Tarlo
2023· book-chapter· en· Elsevier eBooks· Engineering
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Reliability of printed wire bonds
Catherine Marsan-Loyer, Christophe Sansregret
2019· article· en· IMAPSource Proceedings· Engineering
machine prediction:candidate · noneconsensus · none
0
citations

How this was built: Screen · Findings · About