Large variation in ambient gamma-ray backgrounds challenges the search for radiation sources. Raising detection thresholds is a common response, but one that comes at the price of reduced detection sensitivity. In response to this challenge, we explore several trip-wire detection algorithms for gamma-ray spectrometers. We assess their ability to mitigate background variation and find that the best-performing algorithms focus on the spectral shape over several energy bins using spectral comparison ratios and dynamically predict background with the Kalman Filter.