Decision Trace / DTM Archive
This page is an archive of the early research, design concepts, and implementation notes around the Decision Trace Model. The current research framework is now organized at Chinoba.org.
Visit Chinoba.orgWhat is the Decision Trace Model?
The Decision Trace Model, or DTM, is a framework for designing AI systems around explicit decision-making rather than model outputs.
An AI output is not a final decision. It is a signal that supports a decision. DTM separates AI signals, human judgment, boundaries, execution, and logs into a traceable and explainable decision flow.
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Signal
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Decision
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Boundary
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Human
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Execution
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Log
Through this structure, AI systems can move beyond producing outputs and become systems that support, execute, and record decisions.
Decision Trace / DTM Archive
These pages were created before Chinoba.org was organized as the current research site. They preserve the early fixed pages around the Decision Trace Model.
They cover Decision Trace Model, AI decision support, multi-agent coordination, architecture design, and why AI systems often stop before reaching real-world execution. These concepts later became part of the foundation of Chinoba.
Architecture
The system architecture for implementing structured decision-making.
View Architecture →Why AI Stops
Why many AI systems fail to move from output to operational decision-making.
View Why AI Stops →Position in the Knowledge Base
The Knowledge Base is the technical foundation that supports Chinoba research. It connects theory, early design concepts, technical references, and implementation.
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Knowledge Base
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DTM Archive
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Implementation
This page serves as an entry point to the early concepts, fixed pages, and implementation paths that led to the current Chinoba research framework.