# Transport as a General Predictive Architecture **Entity class:** Cross-domain mathematical architecture ## Definition **Transport as a general predictive architecture** is the abstract chain: **source → medium or network → propagation or transmission → exposure → receptor → response → observation → inverse inference → forecast** The chain can recur across physically different domains without making their entities equivalent. In radiation modeling, particle transport equations and reduced-order surrogates are predictive machinery; radiation is the transported quantity; matter and geometry form the medium; a person or asset is a receptor; dose or damage is response; measurements provide observations; inverse methods estimate hidden parameters; and uncertainty quantification qualifies inference. In epidemic modeling, the transported object is infection through contacts. In complex-contagion models of radicalization, the transmitted content is informational and social, and adoption can require reinforcement. The domain assumptions, causal mechanisms, evidence rules, and legal consequences differ. ## Evidence Boundary Oden documents radiation prediction and epidemic modeling by Bui-Thanh. Counterterrorism scholarship independently documents epidemiological and network models of radicalization. The generalized architecture is a structural synthesis, not evidence that Oden or DTRA substituted ideological variables into nuclear code. ## Relationships - **physical implementation:** [[wiki/Nuclear Weapon Radiation Effects Modeling|Nuclear Weapon Radiation Effects Modeling]] and [[wiki/Source-Transport-Receptor Chain|Source–Transport–Receptor Chain]]. - **epidemic implementation:** [[wiki/Epidemic Modeling|Epidemic Modeling]] and Bui-Thanh's [[wiki/Machine-Learning-Assisted Real-Time Simulations and Uncertainty Quantifications for Infectious Disease Outbreaks|2020 project]]. - **social analogue:** [[wiki/Ideological Transmission as Complex Contagion|Ideological Transmission as Complex Contagion]] and [[wiki/From Radiation Field to Social Field|From Radiation Field to Social Field]]. - **methods:** [[wiki/Inverse Problem|Inverse Problems]], [[wiki/Reduced-Order Modeling|Reduced-Order Modeling]], and [[wiki/Uncertainty Quantification|Uncertainty Quantification]]. ## Sources / Provenance - [Oden Institute — DTRA radiation-effects project, 2017](https://oden.utexas.edu/news-and-events/news/minimizing-uncertainty-in-uncertain-world-of-defense-energy/) - [Oden Institute — infectious-disease forecasting project, 2020](https://oden.utexas.edu/news-and-events/news/CONTEXTanBuiThanh/)