I think you're using a strange definition of p<x here. p<0.01 does not mean that the phenomena is perfectly understood, merely the likelihood that some independent variable affects some dependent variable in some direction.

For example, global weather is a hugely complex system which is far from fully understood. Let's take an incredibly simple predictive model of temperature: Still, even with the most simplistic model, say, predict the current temperature by just predicting the average temperature for the current season. That's not going to be very accurate, but if you run it for a year it will almost certainly be p<.01.