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However, they do have differences in predictions for lighter targets where measurements also differ from the predictions.
These differences creates differences in predictions of outbreak patterns larger than 40% in terms of cumulative cases.
This relatively narrow range of data may explain some of the differences in predictions between the Acadian FVS model, developed from a much larger regional database, and the I/C model developed here.
Differences in predictions are expected because Stubb reports matches to a prior factor, but does not consider the similarity of different matches to one another; whereas PhyloGibbs-MP reports conserved motifs, scored on the similarity to one another of different sites associated with each motif, and gives secondary importance to a match with a prior PWM.
Differences in predictions between high and lower performers were found on the knowledge test but not on the OSCE.
We found no other significant differences in predictions from the 3 methods in glycolysis, the PPP, anapleurotic, or secretion reactions.
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We focused on four cases that had a significantly different Bayes factor, but marginal differences in prediction accuracy.
The differences in prediction performance of different models reflect the underlying genetic architecture of the traits.
Both systems were shown to predict syneresis without significant differences in prediction accuracy.
One major reason of the minor differences in prediction accuracies among the different models lies in the high level of LD found in elite breeding germplasm of maize.
A recent study on genomic prediction for different traits in loblolly pine indicated generally small differences in prediction accuracy between the models RR-BLUP, BL, BayesA, and BayesC (Resende et al. 2012).
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