Source record

Paper 4 of this series, register entries H5 and H6; Paper 3, Section 5.1 (the survey-model validation loop); NIST AI 100-1 (reliability encompassing resistance to drift and degrada

Method: Literature

Paper 4 of this series, register entries H5 and H6; Paper 3, Section 5.1 (the survey-model validation loop); NIST AI 100-1 (reliability encompassing resistance to drift and degradation).

A Framework for Trustworthy Deployment: Governance, Human-Automation Teaming, and a Phased Implementation Roadmap for AI in Track Base Management

When the Model Is Wrong: Risks, Hazards, and Failure Modes of AI in Safety-Critical Track Inspection

The Economics of Knowing: Predictive Maintenance, Degradation Forecasting, and the Asset Value Case for Substructure AI

A Framework for Trustworthy Deployment: Governance, Human-Automation Teaming, and a Phased Implementation Roadmap for AI in Track Base Management

When the Model Is Wrong: Risks, Hazards, and Failure Modes of AI in Safety-Critical Track Inspection

The Economics of Knowing: Predictive Maintenance, Degradation Forecasting, and the Asset Value Case for Substructure AI

A Framework for Trustworthy Deployment: Governance, Human-Automation Teaming, and a Phased Implementation Roadmap for AI in Track Base Management

When the Model Is Wrong: Risks, Hazards, and Failure Modes of AI in Safety-Critical Track Inspection

The Economics of Knowing: Predictive Maintenance, Degradation Forecasting, and the Asset Value Case for Substructure AI

A Framework for Trustworthy Deployment: Governance, Human-Automation Teaming, and a Phased Implementation Roadmap for AI in Track Base Management

When the Model Is Wrong: Risks, Hazards, and Failure Modes of AI in Safety-Critical Track Inspection

The Economics of Knowing: Predictive Maintenance, Degradation Forecasting, and the Asset Value Case for Substructure AI