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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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Fault Detection and Control Systems
Retraction
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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.

2,467 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.
2,467 works in the cohort · of 4,299,418page 37 of 50

Labels cover 3 of 2,467 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 2,467 of 2,467 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
Faults Forecasting System
Hanaa E. Sayed, Hossam A. Gabbar, Shigeji Miyazaki
2009· article· en· Zenodo (CERN European Organization for Nuclear Research)· Engineering
machine prediction:candidate · noneconsensus · none
1
citations
affunlabeled
Machinery Faults Detection and Forecasting Using Hidden Markov Models
Paolo Calefati, Biagio Amico, Antonella Lacasella, Emanuel Muraca, Ming J. Zuo
2006· article· en· Volume 2: Automotive Systems, Bioengineering and Biomedical Technology, Fluids Engineering, Maintenance Engineering and Non-Destructive Evaluation, and Nanotechnology· Engineering
machine prediction:candidate · noneconsensus · none
1
citations
afffundno abstractunlabeled
Identification of symmetric noncausal processes
Qiugang Lu, Philip D. Loewen, R. Bhushan Gopaluni, Michael G. Forbes, Johan U. Backström, Guy A. Dumont +1 more
2019· article· en· Automatica· Engineering
machine prediction:candidate · noneconsensus · none
1
citations
affunlabeled
ARM Site E36 - CLAMPS 2 AERI / Reviewed Data
Joshua G. Gebauer, Arianna Jordan
2023· dataset· en· OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)· Engineering
machine prediction:candidate · noneconsensus · none
1
citations
affunlabeled
Spectral time-lapse (STL) Toolbox
Christopher R. Madan, Marcia L. Spetch
2014· article· en· Zenodo (CERN European Organization for Nuclear Research)· Engineering
machine prediction:candidate · noneconsensus · none
1
citations
affno abstractunlabeled
Kernel-Based Nonlinear Feature Learning
Haitao Zhao, Zhihui Lai, Henry Leung, Xianyi Zhang
2020· book-chapter· en· Information fusion and data science· Engineering
machine prediction:candidate · noneconsensus · none
1
citations
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