It's not as sophisticated as some of the models we expect to see, but nevertheless it is teaching the executive team to use data to inform people-related decisions.
Estimating RF network models: We expect that RFs will be related to each other in both group networks, but that CA and no-CA networks will be dissimilar in structure.
The Moto X can afford to listen at all times thanks to a low-power coprocessor dedicated to the task, so perhaps Apple's A8 system-on-a-chip will include something similar in the new iPhone and iPad models we expect to hit sometime this fall.
Since context-dependent processing is observed even in these simple, linear models, we expect it to be a general feature of neuronal computation.
Similarly to the network models, we expect to maximize the performance of the connectivity methods by selecting a number of connections near the number of direct connections of a hypothetic SWM of the culture.
Similarly to what obtained on the network models, where the position of the PPC peaks (Figure 4C and 4D) are located near the number of the connections effectively present into the models, we expect to maximize the performances by selecting a number of connections close to the estimated synaptic ones actually present on the experimental data (about 600/700 connections).
Under the second of these models, we expect fewer rare variants within the gene to be causal, since the total MAF is lower.
Thus, as for the JC, K2P, and HKY models, we expect their +gwF variants to remain of interest as part of the hierarchy of simple to complex models for sequence evolution.
In the context of Boolean models, we expect that further development of experimental design (Sharan and Karp, 2012), in intimate coordination with advances in experimental techniques will allow us to tackle this issue.
