An artificial neural network is displayed in the figure below. The network can be described as follows:

The network accepts two inputs, which are denoted x $0$ and x $1.$

There is a single hidden layer containing three nodes. For convenience, we will refer to these nodes as A$,$ B$,$ and C$.$

The bias term for node A is $2\mathrm{.}5.$ The weights for the connections from x $0$ and x $1$ to A are $0\mathrm{.}6$ and $-0\mathrm{.}3,$ respectively.

The bias term for node B is $-4\mathrm{.}9.$ The weights for the connections from x $0$ and x $1$ to A are $-0\mathrm{.}4$ and $0\mathrm{.}7,$ respectively.

The bias term for node C is $3\mathrm{.}8.$ The weights for the connections from x $0$ and x $1$ to A are $0\mathrm{.}5$ and $0\mathrm{.}2,$ respectively.

The nodes A$,$ B$,$ and C all use ReLU activations.

There is a single output node.

The bias term for the output node is $1\mathrm{.}3.$ The weights for the connections from $A,B,$ and C are $0\mathrm{.}4,0\mathrm{.}6,$ and $-0\mathrm{.}2,$ respectively.

The output node uses the sigmoid activation.

Calculate the output of the neuron for the inputs shown below. Round your answer to four decimal places.

$x0=5,x1=8$