Sentence examples for models were higher from inspiring English sources

R2 values of the established models were higher than 0.844, indicating that models were adequate to predict HMF content.

In addition, the sensitivities of all classification models were higher than 87%, indicating that the pre-trained machine learning models are sensitive when identifying older people who are at high risk of falling.

The design floods determined by the unit hydrograph models were higher than those predicted by the rational method applied in this study.

Overall these predictive performance from the ARMAX time series models were higher than almost all the previous studies we are aware.

Among them, the probabilities of 19 models were higher than 0.005.

Most of the prediction accuracies of the LLR, SA, SR, and GP consensus models were higher than those of the reference (e.g., R2 of "Set_2896" is 0.545 for GP versus 0.42 for the reference consensus model).

The correlation coefficient values for the models were high (>0.99).

The cost of the best models is higher ($750 to $999), but so is their quality.

It shows that GSSR models are higher in precision and more complex compared with GSR models.

The sensitivity of FSP + CVHI + inflammatory cytokine and CVHI + inflammatory cytokine models was higher than 90%.

The contributions using multiple regression models are higher than are the ones for single regression models.