Fig. 3

Model training and testing process. (1) data splitting: the original dataset (n = 1970) were randomly divided into two equal sized subsets of fragments (n = 985): one to be used for model training and the other for model testing. (2) the model training process implies a 10 × 10 cross-validation and provides the best fit model. (3) Posterior predictive values of the model were estimated from cross-validation resampling process. (4) Finally, the model was tested against external subset (n = 985). Model’s performance metrics were evaluated