## 3 Results  
Figure 4 presents the scatter plots of the lower bound (SF-LB) and upper bound (SF-UB) safety factors. Similar behavior is observed in both cases. Behavioral models (BM) are mainly observed when the inclination angle (\(\beta\)) is less than 50\({}^{\circ}\). In the case of slope height (\(H\)), BM are observed along all the ranges studied; however, the number of BM increases with lower H values. In the case of cohesion (\(c\)) and friction angle (\(\phi\)), BM are associated with high \(c\) and \(\phi\) values. Meanwhile, safety factor sensitivity to unit weight (\(\gamma\)) is not observed. Figure 4: Scatter plots of the SF as a function of each analyzed parameter for the lower bound (SF-LB) (**a**) and upper bound (SF-UB) (**b**). Blue dots represent behavioral models (BM) and red dots non-behavioral models (N-BM). The representation of both lower bound and upper bound safety factors in Figure 4 shows similar distributions for each parameter on the two datasets. Figure 5 presents the cumulative distribution functions (CDF) for SF-LB and SF-UB, grouped into deciles from the most stable 10% of the models (greater SF, brown) to the least stable 10% of the models (lower SF, blue). It is observed that the most stable 10% of the models (SF \(>\) 1.4) are clustered at lower height values (\(H\)) and, in general, at \(H\) < 10 m (P50 = 10 m). In contrast, the least stable 10% of the models are concentrated above 10 m. Although SF-LB and SF-UB decrease as H increases, stable models (SF \(>\) 1.2) can be obtained when \(H\) > 20 m (P90 = 20 m). Regarding slope angle (\(\beta\)), it is observed that the lower the slope inclination angle, the greater the SF, with the most stable 10% of the models (SF \(>\) 1.4) concentrated at \(\beta\leq 39.5^{\circ}\) (P90). Meanwhile, the least stable 10% of the models occur over 53\({}^{\circ}\). It is also noted that SF-LB and SF-UB increase when cohesion is greater than 2 kPa (\(c>\) 2 kPa), with the most stable 10% of the models (SF \(>\) 1.4) concentrated above that value. Alternatively, the least stable 10% of the models are clustered at values of \(c<\) 2 kPa (P80). For the friction angle (\(\phi\)), the most stable 10% of the models (SF \(>\) 1.4) are concentrated above 31.6\({}^{\circ}\) (\(\phi>\) 31.6\({}^{\circ}\)), while the least stable 10% of the models are obtained for \(\phi<31.6^{\circ}\). The unit weight does not present a particular concentration of models for each group. Figure 5: Cumulative distribution function by deciles of model behavior for (**a**) lower bound (SF-LB) and (**b**) upper bound (SF-UB). Figure 6 presents a parallel coordinates plot for the lower bound and upper bound SF, grouped by deciles from the most stable 10% of the models (greater SF, brown) to the least stable 10% (lower SF, blue). This plot indicates how the variable values are related to each other according to the performance of the analyzed models. As with the CDF, the SF-LB and SF-UB parallel coordinates plots are similar. Regarding the most stable 10% of the models (SF-LB and SF-UB > 1.4), parameter behaviors are identified. First, stable models are observed throughout the range of H variability (0-30 m), associated mostly with \(\beta\) values lower than 39.5\({}^{\circ}\). However, it is also possible to find models among the most stable 10% in the range of 39.5\({}^{\circ}\) to 53\({}^{\circ}\) and a small number between 53\({}^{\circ}\) and 66.5\({}^{\circ}\). This behavior is attributed to cohesion, friction angle, and unit weight, as a concentration of models is observed when \(c>2.5\) kPa, \(\phi<33.8^{\circ}\), and 18 kN/m\({}^{3}<\gamma<21\) kN/m\({}^{3}\). Meanwhile, another group of stable models is observed for slopes with \(c<2.5\) kPa, \(\phi>33.8^{\circ}\), and \(\gamma<19\) kN/m\({}^{3}\). Figure 6: Parallel coordinates plot for (**a**) lower bound (SF-LB) and (**b**) upper bound (SF-UB) safety factors. Figure 7 presents the boxplots of the sensitivity index calculated for each factor.