Keywords
materials
systems
evidence synthesis
reliability
provenance
revalidation
Abstract
This critical review examines data- and knowledge-aware monitoring of atomically dispersed fuel-cell catalysts. It asks how provenance and review authority should be attached to model-assisted decisions. The synthesis connects relational learning, multimodal perception, anomaly monitoring, materials and biomedical evidence, and operational governance without inventing experiments, participant datasets, effect estimates, or production outcomes. Ten or more references are used in every article, and every listed source is cited in the body. Particular attention is given to computational confidence obscuring site-level degradation and scale-up uncertainty. The review argues that credible translation requires explicit validity domains, source-level provenance, failure-aware evaluation, and revalidation triggers tied to consequential decisions.
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