US US20260050715A1
[0000] A computing system obtains multiple factors for a first environment in a first experiment. The multiple factors include one or more profile factors and one or more subject factors. Each profile factor of the one or more profile factors specifies multiple candidate features for the first environment. Each subject factor of the one or more subject factors specifies multiple candidate levels categorizing different subjects interacting with the first environment. The computing system obtains a predictive model for predicting probabilities of multiple candidate outcomes for the first environment. The predictive model has weighted model terms. The computing system receives a selection of a first level for a first subject factor of the one or more subject factors. The computing system generates a computer-generated representation of a fixed-factor model. The fixed-factor model predicts multiple candidate outcomes for a second environment with subjects defined by the selection of the first level.
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