A model compresses a state space by capturing a set of invariances that predict the variance in the states. Its free parameters define the latent space of the model and should ideally fully correspond to the variability, the not-invariant (= unexplained) remainder of the state.
Your confidence must equal the weight of the evidence. This includes the confidence in the way you think, too. You cannot put more confidence in your conclusion than in the logical operator itself.
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Is confidence the model-holder's prediction of the model's relationship to 'the truth'? Is it a number or a distribution of possible outcomes? Can we compare the confidence value to it's 'actual' truth? Or are they different ideas about a model? (This is a lot of questions....)
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