<｜begin▁of▁sentence｜>### Instruction:
As a management consultant, I offer strategic guidance and expertise to organizations aiming to enhance their operations and achieve growth and success. Suppose you have a network of collaborations among astrophysics researchers stored in a GML file named astro-ph.gml. If you are seeking to leverage the EnDNTM algorithm within the cdlib library for overlapping community detection using ensemble approaches with distributed neighborhood threshold methods, and then want a JSON representation of the resulting NodeClustering object, I can provide insights into this complex data analysis process.
### Response:
from cdlib import algorithms
import networkx as nx

# Load an Astrophysics collaborations graph
G = nx.read_gml('astro-ph.gml')

# Compute base partition using crisp community detection algorithms
base_partitions = [algorithms.louvain(G), algorithms.label_propagation(G), algorithms.walktrap(G)]

# Use EnDNTM to detect overlapping communities based on the base partitions
overlapping_communities = algorithms.endntm(G, base_partitions)

# Convert the NodeClustering object to a JSON format
communities_json = overlapping_communities.to_json()

# Output the JSON object
print(communities_json)
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