A statistic; square root of the mean of the squares.
1Much improved curve fitting was achieved for all UTE-Cones biomarkers with greatly reduced root mean square errors.
2After image correction, the root mean square (rms) deviations of the reference points of each image were calculated.
3The mean root mean square was significantly lower in group A than in group B (P = .007).
4Within each lobe, root mean square deviations in Calpha positions averaged approximately equals 0.9 A.
5The average root mean square error of the model's predictions of sagittal motion was equal to 0.1 deg.
6The root mean square deviation for heavy backbone atoms within the helices was 0.64 A in 55 structures.
7The best GA-PLS model was characterized by the value of root mean square error of prediction RMSEP = 0.108 logarithmic Pascal units.
8We determined a high-resolution structure of CKR-brazzein by nuclear magnetic resonance spectroscopy (backbone root mean square deviation of 0.39 Å).
9A similar trend was noticed for root mean square where nickel-titanium (p = 0.014) and beta-titanium (p = 0.013) had increased root mean square.
10The reliability of the examiner using the ICON was assessed using Root Mean Square.
11Root Mean Square Error (RMSE) of image is calculated to study the convergence of reconstructed images compared with the truth image.
Translations for root mean square