Structural Asymmetry Diagnostic Architecture (SADA): A Symmetry-Based Diagnostic Framework for Research Decision Architectures Under Uncertainty

Complex decision-making environments are commonly evaluated through output performance, while the structural coherence of the underlying decision architecture remains insufficiently examined. This study introduces the Structural Asymmetry Diagnostic Architecture (SADA), a symmetry-based framework for evaluating structural stability in research decision architectures under uncertainty. The proposed model formalizes the interaction between methodological complexity, uncertainty exposure, and validation capacity through the Imbalance Coefficient (Δ) and the generalized Research Stability Index (RSIα,β). An analytical evaluation of structural configurations, combined with a comparative benchmark against representative MCDM and uncertainty-aware methods, shows that structural symmetry is a necessary condition for robustness, whereas validation capacity acts as a feasibility-enabling factor rather than a compensatory mechanism for severe asymmetry. The results indicate that ranking consistency alone does not guarantee structural robustness, as configurations with acceptable ordinal behavior may remain fragile when methodological complexity and uncertainty exposure are misaligned. SADA therefore operates as a pre-decisional diagnostic layer that complements classical decision-making methods by assessing architectural coherence before outcome interpretation. The framework is interpretable, dimensionless, and compatible with broader uncertainty-aware paradigms, offering a structural perspective on robustness as an emergent property of symmetry preservation under constrained validation.