Scores are not absolute, and only have meaning relative to other scores in the same request. LUIS training is non-deterministic, so between versions, and even between exporting and re-importing the exact same version of the app, an application and its models will not necessarily return the exact same scores. Your system should use the highest scoring intent regardless of its value. For example, a score below 0.5 does not necessarily mean that LUIS has low confidence. Providing more training data can help increase the score of the most-likely intent.