<｜begin▁of▁sentence｜>### Instruction:
Imagine you're part of an initiative to foster interconnectedness within a diverse organizational community, visualizing the relationships like a simple network where points (or nodes) represent individuals and lines (or edges) symbolize mutual collaborations. The current interactions can be depicted as connections between points: (0 with 1), (0 with 2), (1 with 2), (1 with 3), and (2 with 3). To enhance inclusivity, you are considering a hypothetical expansion strategy similar to constructing a Mycielskian of this network—a creative method to potentially double the number of interactions without generating direct competition, that is, not duplicating any existing connections.

Could you create a model of this theoretical inclusive network, and provide the anticipated total of members (nodes) and collaborative pairs (edges) in this expanded scenario, given the initial network structure described? Keep in mind, this is purely for exploratory planning, providing a way to visualize potential growth while respecting existing relations.
### Response:
import networkx as nx

# Create a simple, undirected graph G
G = nx.Graph()
G.add_edges_from([(0, 1), (0, 2), (1, 2), (1, 3), (2, 3)])

# Perform the Mycielski operation
M = nx.mycielskian(G, iterations=1)

print('The Mycielskian graph has %d nodes and %d edges.' % (M.number_of_nodes(), M.number_of_edges()))
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