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Table 1 Comparison of size of predicted data Study Prediction size (h) Ref. [20] 50 Ref. [21] 50 Ref. [16] 45 Present study 1,314.
In our study, prediction substantially improved by using genetic parameters in the predictive models.
In the second stage of the study, prediction models through gene expression programming (GEP) and multiple linear regression (MLR) were derived.
For this study, prediction of turbidity during streamflow events is based upon observed data (e.g., measured streamflow, precipitation and air temperature).
Conclusion: Because of the low number of patients involved in this study, prediction of therapeutical success based on the quasispecies complexity was not possible.
Sound environment reproduction of various flight conditions in aircraft mock-ups is a valuable tool for the study, prediction, demonstration and jury testing of interior aircraft sound quality and annoyance.
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To test the interview we determined a priori several study predictions about children's pain experiences.
In this study, predictions based on sufficient probe set size and fold-change are confirmed by independent means.
To confirm our two study predictions and to compliment the exploratory ICA approach, specific pairwise CCAs for key regions of the 'paralimbic' and 'default mode' RSNs were performed.
The results were in line with the study predictions.
CALINE4 predictions accounted for key factors that determine exposure, such as wind speed and direction, and the CHS ICV study predictions offered a further refinement of the exposure surface.
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