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To this end, it is important to identify a value chain that does not only have a high potential for increased productivity, but already includes targeted groups.
The central idea of the MAVT is to identify a value function for each sector to compute the satisfaction (with respect to the sector criterion) for the effects that each alternative produces.
Until a generic theoretical mapping between C p and C b has been established however, we here provide a pragmatic solution: On a training dataset for which input functions are available, identify a value for α so that perfect agreement between V ND estimated with Logan plot and 2TCM is obtained.
We propose two alternatives, both of which identify a value specific to subsample k (i.e., local): complement deviance selection and permutation selection.
We found that this heuristic rule allowed us to identify a value of tp, which often (8 out of 9 networks tested) corresponded to the highest AUC values within a tolerance of 5%.
The 1.5% value was chosen on the basis of a review of the ROC curve (to roughly identify a value balancing sensitivity and specificity) and because it approximates the in-hospital mortality rate seen in patients with PE at very low risk and low risk (classes I and II) in the original PESI derivation study.
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But a handful have identified a value and developed applications for specific communities.
It identifies a value that a governance structure might realize.
Identifying a value and its unit is simple.
The agreement between modeling and experimental data identified a value for the friction coefficient of 0.065.
Meanwhile, level identifies a value for each feature of the signal pattern.
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