The WQI predictions of this model had significant, positive, very high correlation (r = 0.977, p < 0.01) with the measured WQI values, implying that the model predictions explain around 95.4% of the variation in the measured WQI values.
The neural predictions explain about 76% of the variation in individual pitch percepts (Figure 3f, df = 1,108; F = 336.3, p<0.0001); for population data, the neural pitch predictions explain about 99.8% of the variation in subjective percepts with a regression line slope of 1.0 (Figure 3g, df = 1,3; F = 1614.0, p<0.0001614.0,
(B and C ) Extent to which the predictions explain the mRNA fold changes observed in the test set.
Using a cross-validation approach, genomic predictions explained ~32% of the variation in yield phenotypes.
Thus, for the application of Eq. (13) to substantial earthquake data, it was necessary to check the extent to which the time-harmonic wave predictions explained the amplitude level variance for non-time-harmonic waves.
These predictions explained more than half of the variance in learning success among individuals, suggesting that individual differences in neuroanatomy or persistent physiology predict whether and to what extent people will benefit from training in a complex task.
This significant reduction in the number of false-positive predictions explains the large increase in the sPPV values.
In a previous study, we showed that this transition is predicted to occur at the level of the LFP from the network model, and also that these predictions explained observations in human MEG data (Hunt et al., 2012).
In our model of eve 3+7, including a quadratic term for concentration-dependent dual regulation produces better wild-type predictions, explains experimental perturbations accurately (with certain assumptions), and produces consistent fits across different training subsets.
However, many human and mouse NMIs have lower CpG O/E and GC content than the CGI predictions, explaining why the CGI predictions do not accurately identify all NMIs in these species.
