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Updated: Jan 28, 2026

Automated Detection and Analysis of Exocytosis
Published on: September 11, 2021
Extending Three Existing Models to Analysis of Trust in Automation: Signal Detection, Statistical Parameter
1Massachusetts Institute of Technology, Lexington, USA.
Objective:
The objective is to propose three quantitative models of trust in automation.
Background:
Current trust-in-automation literature includes various definitions and frameworks, which are reviewed.
Method:
This research shows how three existing models, namely those for signal detection, statistical parameter estimation calibration, and internal model-based control, can be revised and reinterpreted to apply to trust in automation useful for human-system interaction design.
Results:
The resulting reinterpretation is presented quantitatively and graphically, and the measures for trust and trust calibration are discussed, along with examples of application.
Conclusion:
The resulting models can be applied to provide quantitative trust measures in future experiments or system designs.
Applications:
Simple examples are provided to explain how model application works for the three trust contexts that correspond to signal detection, parameter estimation calibration, and model-based open-loop control.
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