DEGA: A Deterministic Diagnostic Evidence Governance Agent for Industrial IoT—A DUDU-BLDC Case Study

Abstract excerpt

Industrial diagnostic systems increasingly combine machine-learning classifiers, temporal models, uncertainty surrogates, and explanation methods. Their operational use requires a separate mechanism that determines whether the available evidence is valid, mutually consistent, sufficient for a recommendation, or should instead lead to abstention or human escalation. This paper introduces the Diagnostic Evidence Gov...

Topics

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• Artificial Intelligence
• Benchmarking
• Bioinformatics and Genomic Networks
• Electronic Health Records
• Phenotype
• Primary Health Care
• Sensitivity and Specificity
• Software

Identifiers and source

Literature Corpus work

ff969d6a-6dfa-5eb7-a791-1c77294766af

DOI

10.20944/preprints202607.1415.v1