<｜begin▁of▁sentence｜>### Instruction:
Certainly! Imagine you're assisting a manager in visualizing and analyzing the interconnectedness within a network of five team leaders (represented as a complete graph with nodes 0 through 4). The manager is particularly interested in the strength of the working relationships between two pairs of team leaders: Leader 0 and Leader 1, and Leader 2 and Leader 3.

To provide the insights your manager needs, you are asked to calculate the Common Neighbor and Centrality based Parameterized Algorithm (CCPA) score for these pairs of leaders. This score will help in understanding the potential for collaboration and information flow between them.

This scenario involves no specific data or gml file, but if you had access to such data or a file named, for example, "team_network.gml," you would be expected to reference this file within the context of your task.
### Response:
import networkx as nx

# Create a complete graph with 5 nodes
G = nx.complete_graph(5)

# Compute the Common Neighbor and Centrality based Parameterized Algorithm (CCPA) score
# for the pairs of nodes (0, 1) and (2, 3)
preds = nx.common_neighbor_centrality(G, [(0, 1), (2, 3)])

# Print the CCPA scores
for u, v, p in preds:
    print(f"({u}, {v}) -> {p}")
<|EOT|>
