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We follow McPhee in measuring the semantics of a subtree using the fitness cases.
There are three kinds of fitness functions for the classic GEP method, and this paper adopts the fitness function based on the absolute error: (1) f i = ∑ j = 1 n (R − | P (i j ) − T j T j · 100 | ), where R is the selection range, P ij ) is the predicted value by the individual program i for fitness case j (out of n fitness cases), and T j is the target value for fitness case j.
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In the Octane Fitness case, the five judges appointed by Republican presidents, including Judge Rader, split 3-to-2 in favor of the patent holder and against Octane Fitness.
Firstly, mutator mechanisms predominate in most instances, although the value of α50% increases slightly compared to the constant fitness case (Supplementary Table S1 and Figure 2).
These first D steps can therefore be analyzed using the strategy previously outlined for the non-mutator pathway in the constant fitness case [15].
These first D steps, with or without a mutator mutation, can therefore be analyzed using the strategy previously outlined for the constant fitness case [15].
In the constant fitness case, the probability of having C oncogenic mutations at time T is derived for the non-mutator pathway based on minimal assumptions.
As in the constant fitness case [15], and the incremental lineage expansion case (case 1 above), we approximate mutator pathways by considering mutator mutations occurring as an initial step in tumorigenesis.
Based on the analytical model, the relative efficiency Nrel 1∶0 is reduced in the case of incremental lineage expansion by a factor of RT (C−1)/[(C+1 C] compared to the constant fitness case.
As in the incremental lineage expansion case, the calculations show a slight increase in α50% relative to the constant fitness case, while still generally indicating a predominance of mutator pathways.
When judged by relative efficiency Nrel 1∶0, the importance of mutator pathways is reduced relative to the constant fitness case to a greater degree than one would judge based on α50%.
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