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The rapid evolution of wearable sensor hardware across successive device generations introduces systematic signal drift that undermines the reliability of clinical-grade physiological sensing in real-world healthcare ecosystems. This conceptual systems research article proposes a novel architectural solution to the persistent challenge of calibration transfer without empirical retraining or device-specific fine-tuning. We introduce the cross-generation calibration orchestration and transfer infrastructure (CG-COTI) — a theoretical multi-layer generalization framework specifically engineered for clinical sensing. CG-COTI establishes a device-agnostic calibration lattice that propagates standardized physiological representations across hardware generations through orchestrated metadata-driven mapping, federated drift governance, and closed-loop intelligence layers. Three interpretive conceptual formulations are advanced: a risk-propagation index capturing cumulative sensor drift in multi-generational deployments, a decision-confidence decay function under uncalibrated generational shifts, and a governance-load equilibrium equation balancing monitoring burden with clinical safety. Positioned within existing EHR intelligence ecosystems and decision-support pipelines, CG-COTI offers a scalable architectural blueprint for seamless interoperability, regulatory-compliant deployment, and sustained analytical fidelity. By anchoring calibration transfer within clinical governance and workflow integration models, the framework eliminates the need for repeated device-specific recalibration while preserving signal integrity essential for continuous patient monitoring, early deterioration detection, and precision therapeutics. This purely conceptual architecture advances the theoretical foundations of wearable-enabled healthcare systems, providing a reusable infrastructural scaffold for next-generation clinical sensing deployments across heterogeneous device fleets.