{'fraction_non_alphanumeric': 0.015804597701149427, 'fraction_numerical': 0.0, 'mean_word_length': 5.514018691588785, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Characterising uncertainty in instrumental limits of detection when sensor response is non-linear

Consistent reporting of Limit of Detection (LOD) and its inherent uncertainty is imperative as the number of sensors for challenging applications continues to rise. Here, we demonstrate a Bayesian approach to LOD estimation, which also provides estimates of LOD uncertainty. By using this method to compare seemingly similar sensors, we demonstrate that LOD uncertainty is at least as important as LOD point estimates when determining the suitability of a sensor for a stated application. By including LOD uncertainties when describing new techniques, we can more objectively evaluate new sensors.