AI 中文总结
研究针对数字化辐射传感器衰变数据集，提出可重复的简化数据工作流程，通过加权指数拟合及考虑多种图形级效应来测试半衰期估计，展示了如何在有限信息下测试数据的可重复性、可识别性及对分析选择的敏感性。
AI 中文摘要
准确解读辐射传感器衰变数据对环境监测、场地修复、辐射计量、探测器质量保证和核数据评估至关重要。当原始伽马能谱记录不可用时，已发表的衰变图可能是唯一可独立重新分析的来源。本研究提出了一种可重复的简化数据工作流程，用于测试数字化的198 - Au衰变数据集的半衰期估计。对数字化数据点进行加权指数拟合可重现已发表的室温半衰期，表明主要衰变尺度保留在图形级数据集中。接着分析了拟合结果在合理的图形级效应下如何变化，包括类似基线的偏移、时间轴重建、有限窗口影响和基于比率的稳健性检查。无偏移拟合在局部受良好约束，但小的恒定偏移会使拟合的半衰期发生变化。玩具蒙特卡罗诊断表明，对于有限窗口指数数据，预计会有一些估计器偏移。本研究未修订推荐的核数据或取代原始实验。相反，它展示了在仅提供简化或图形级信息时，如何测试已发表的辐射传感器衰变数据的可重复性、可识别性以及对分析选择的敏感性。
英文摘要
Accurate interpretation of radiation-sensor decay data is important for environmental monitoring, site remediation, radiation metrology, detector quality assurance, and nuclear data evaluation. When the original gamma-spectrometry records are unavailable, a published decay plot may be the only source that can be reanalyzed independently. This study presents a reproducible reduced-data workflow for testing half-life estimates from a digitized 198-Au decay dataset. A weighted exponential fit to the digitized data points reproduces the published room-temperature half-life, indicating that the main decay scale is retained in the figure-level dataset. The analysis then tests how the fitted result changes under plausible figure-level effects, including baseline-like offsets, time-axis reconstruction, finite-window leverage, and ratio-based robustness checks using pairwise summaries and Steiner's most frequent value statistics. The no-offset fit is locally well constrained, but small constant offsets can shift the fitted half-life because the normalization, decay constant, and residual baseline are partly degenerate over the limited time window. Toy Monte Carlo diagnostics show that some estimator shifts are expected for finite-window exponential data. This study does not revise recommended nuclear data or replace the original experiment. Instead, it shows how published radiation-sensor decay data can be tested for reproducibility, identifiability, and sensitivity to analysis choices when only reduced or figure-level information is available.
Comments39 pages, 7 figures. Published in Sensors, 2026, Volume 26, Article 5056. The journal article is the version of record
Journal refSensors 2026, 26, 5056
