<｜begin▁of▁sentence｜>### Instruction:
As a physical education teacher, you instruct students in physical fitness, sports, and recreational activities. Now, imagine you have a class of students who are participating in a team-building activity. You want to divide them into groups based on their interests and interactions. In order to do this, you have access to a network of the students and their interactions. You have a GML file named "power.gml" that contains the network data, representing the connections between the students. Using this data, you will use the "lemon" function in the Community Detection Library (cdlib) to perform community detection. Additionally, you have identified specific students (labeled '0', '2', and '3') as seed nodes, and you want to use this information to form the communities. Finally, you are tasked with providing the JSON representation of the detected communities in order to facilitate the successful completion of the team-building activity.
### Response:
import networkx as nx
from cdlib import algorithms

# Load a Power grid graph
G = nx.read_gml('power.gml')

# Define seed nodes for the LEMON algorithm
seeds = ['0', '2', '3']  # Note: Actual node labels should be used

# Apply the LEMON community detection algorithm
communities = algorithms.lemon(G, seeds, min_com_size=20, max_com_size=50, expand_step=6, subspace_dim=3, walk_steps=3, biased=False)

# Convert the NodeClustering object to JSON
lemon_json = communities.to_json()

print(lemon_json)
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