Some test must be applied to the low-level count data from alpha continuous air monitors (CAMs) to determine if the count is statistically significant (i.e., significantly above background). The method should be as sensitive as possible, automatically desensitizing when required due to radon progeny, yet in such a manner as to not exceed an acceptable false-alarm rate. The test that has been historically used within many alpha CAMs to accomplish these goals is the so-called sigma factor approach. In this paper, this approach is discussed with respect to four common CAM algorithms. These algorithms are referred to as the theoretical best possible algorithm, the 4-ROI algorithm, the tail-fitting algorithm, and the peak-fitting algorithm. Relative sensitivities are estimated for each algorithm.

中文翻译：

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Alpha CAM 中的 Sigma 因子警报方法的技术细节。

必须对来自阿尔法连续空气监测器 (CAM) 的低水平计数数据进行一些测试，以确定计数是否具有统计显着性（即显着高于背景）。该方法应尽可能灵敏，在需要时因氡子体而自动脱敏，但以不超过可接受的误报率的方式进行。历史上在许多 alpha CAM 中用于实现这些目标的测试是所谓的 sigma 因子方法。在本文中，该方法针对四种常见的 CAM 算法进行了讨论。这些算法被称为理论最佳可能算法、4-ROI 算法、尾部拟合算法和峰值拟合算法。估计每种算法的相对灵敏度。