"substantial prediction" is a correct and usable phrase in written English.
It refers to a significant or meaningful forecast or estimation of something that may happen in the future. Example: "The weather forecast made a substantial prediction of heavy rainfall over the weekend, prompting residents to prepare for potential flooding."
However, the highly volatile and stochastic behaviour of the RTG crane demand creates a substantial prediction challenge.
In a small fictitious example with independent experts, otherwise, we demonstrate that this subjectivity can easily lead to substantial prediction bias, and that the subjective choice of distribution shapes has a similar relevance as uncertainties due to physical conceptualization, numerical codes and parameter uncertainty.
The Cox model based on clinicopathologic parameters offered substantial prediction power as shown in Figure 1.
The bias occurred because EBV of individuals in the testing and the training sets had substantial prediction error correlations.
In particular, Superpc and Unicox are the only algorithms that produce models with substantial prediction performances when trained on the MSK study.
CHIN suggests a critical value of 0.67 for substantial predictions [49].
eLife welcomes theoretical and modeling papers in all areas of biology, especially papers that report new biological insights, make substantial predictions that can be tested, or help to resolve contradictory empirical findings.
The McKenzie algorithm accurately predicts the mean group EQ-5D, but this may be due to its substantial under prediction in good health states (it performs worst in observed EQ-5D values of greater than 0.75) which may offset the over prediction which still occurs in the poorer health states.
The curves zoom on FPR values <0.1, which is motivated by the imbalanced nature of our dataset; i.e. higher FPR would result in substantial over-prediction of MoRFs.
While it is not possible to precisely identify the false positive predictions (predicted amino acid sequences that are not real proteins) from these data, it is clear that the rate of false positive predictions must be substantial for each prediction method.
There is a substantial variation in prediction accuracy between the different molecules in our dataset.
