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The non-cross-validated models exhibited standard errors of regression (sFIT) ranging from 0.279 to 0.398, corresponding to r2 values between 0.901 and 0.827.
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The CoMFA models exhibited a good predictiveness on these ligands with conventional r2 0.469 and standard error of estimation 0.372 as the data described in Table 7.
These two models exhibited largest correlation coefficients R2 (0.98 for model 3AT and 0.99 for model 6AM), smallest standard errors S (0.02 for model 3AT and 0.01 for model 6AM), and smallest Mallow Cp values (3 for both model 3AT and 6AM) among three models in each group.
These two models exhibited largest correlation coefficients R2 (0.98 for model 3AT and 0.99 for model 6AM), smallest standard errors S (0.02 for model 3AT and 0.01 for model 6AM), and smallest Mallow Cp values (3 for both model 3AT and 6AM) among three models in each group. .
All five models exhibited excellent prediction performances.
All other models exhibited acceptable model fit (P > 0.05).
The k-ε Standard and k-ε Realizable models exhibit the best agreement with the experimental data, while the standard k-ω model gives more inadequate results for the investigated configurations.
Material models exhibiting softening behavior and stiffness degradation often lead to severe convergence difficulties in implicit analysis programs, such as Abaqus/Standard.
Best models exhibit normalized RMSE of 7%%.
Both mouse models exhibit increased prostatic branching.
The model exhibited modest residual spatial autocorrelation.
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