Having established the limits of validity for gentle ensemble refinement, we now show that already gentle refinement substantially improves the agreement between simulation and experiment. This improvement is illustrated by the L-curves defining Pareto fronts for Bayesian ensemble refinement (Figure ). The L-curve consists of the optimal χ 2 values divided by the number datapoints M plotted against the optimal KL divergence values S KL for different θ values. The three chosen θ values (100,10,1) cover the elbow regions of the respective L- ), used in BioEn (black) to its approximation (dashed red line) given by half the variance of the reduced energy change β∆U , Eq. ( ), and to its alternative definition SKL(q||p) (dashed-dotted cyan line), Eq. ( ). We show results for the double-well system (top), the polymer mode (middle), and Ala5 (bottom). The bottom panels show the relative difference of -varp(∆u) (red dashed) and SKL(q||p) (cyan dot-dashed) with respect to SKL(p||q) = -⟨∆u⟩p. The approximations roughly start deviating from the values given by the exact expression at (θ, SKL) ≈ (10, 0.17) for the doublewell system, (θ, SKL) ≈ (10, 0.26) for the polymer model, and (θ, SKL) ≈ (1, 1.43) for Ala5. For smaller θ values, we leave the regime of gentle refinement. Vertical lines indicate θ = 100 (blue), 10 (orange), and 1 (green).