Windows-Based Deviation Localization A Measurement Application within the Senmatruis Black Box

This publication documents a measurement application within the Senmatruis Black Box, focused on Windows-based observation under a fixed, previously validated zero reference. The purpose of this work is not to remove or suppress noise, but to localize deviations and describe how their visibility and behavior change across different temporal scales, while keeping calibration fixed and the system closed. Windows are used strictly as an observational lens. They do not recalibrate the system, revalidate the zero reference, or introduce adaptive thresholds. Instead, they make scale-dependent behavior explicit: what becomes visible at short windows, what stabilizes at longer windows, and what persists across scales. The application produces reproducible outputs (labels, metrics, metadata) that allow domain specialists to decide what should remain, what may be filtered, and what requires further investigation. All intervention decisions are deliberately left outside the scope of this work. This publication does not propose a new denoising algorithm, universal filter, or physical law. Its contribution is methodological: localization before intervention, enabling informed and responsible downstream processing.