  We synthesize the knowledge present in various scientific disciplines for the
development of semiparametric endogenous truncation-proof algorithm, correcting
for truncation bias due to endogenous self-selection. This synthesis enriches
the algorithm's accuracy, efficiency and applicability. Improving upon the
covariate shift assumption, data are intrinsically affected and largely
generated by their own behavior (cognition). Refining the concept of Vox Populi
(Wisdom of Crowd) allows data points to sort themselves out depending on their
estimated latent reference group opinion space. Monte Carlo simulations, based
on 2,000,000 different distribution functions, practically generating 100
million realizations, attest to a very high accuracy of our model.
