<｜begin▁of▁sentence｜>### Instruction:
As an IT Project Manager, you have been tasked with analyzing the neural network of the C. elegans organism. The organization has provided a GML file named celegansneural.gml, which contains the network data. You are required to use the wCommunity function in the cdlib library to perform community detection while accounting for edge weights. Additionally, you need to generate a JSON representation of the detected communities. How would you approach this task, ensuring that edge weights are considered during community detection?
### Response:
import networkx as nx
from cdlib import algorithms

# Read the graph from a GML file
G = nx.read_gml('celegansneural.gml')

# Set default edge weight attribute if it's not present
if not nx.get_edge_attributes(G, 'weight'):
    nx.set_edge_attributes(G, values=1, name='weight')

# Perform community detection using wCommunity algorithm
communities = algorithms.wCommunity(G, min_bel_degree=0.6, threshold_bel_degree=0.6)

# Generate JSON representation of the detected communities
communities_json = communities.to_json()
print(communities_json)
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