<｜begin▁of▁sentence｜>### Instruction:
As a seasoned Clinical Dietitian, consider that you're assessing a patient's dietary journey, where each meal choice (represented by nodes) is connected by a pathway of nutritional value (represented by weighted edges). The patient starts their diet plan at node 0 (breakfast), and the goal is to create a sequence of meals that cumulatively contribute to their overall health without exceeding a specific dietary threshold (total weight greater than 10).

In this context, envision you're tasked with outlining a meal plan guideline that finds the most nutritionally efficient path from breakfast (node 0) to subsequent meals, ensuring the combined nutritional value doesn't surpass the prescribed limit. Utilizing a technique analogous to Dijkstra's algorithm, could you delineate the meal routes that present the optimal nutritional continuity while adhering to the patient's dietary constraints? The meal choices and their corresponding nutritional values are detailed in the connections: breakfast to snack (0, 1, 3), snack to lunch (1, 2, 7), lunch to afternoon tea (2, 3, 2), and afternoon tea to dinner (3, 4, 1).
### Response:
import networkx as nx

# Create a weighted graph
G = nx.Graph()
G.add_weighted_edges_from([(0, 1, 3), (1, 2, 7), (2, 3, 2), (3, 4, 1)])

# Compute the shortest path from source node using Dijkstra's Algorithm
cutoff_value = 10  # Optional: Maximum path length to consider
path = nx.single_source_dijkstra_path(G, source=0, cutoff=cutoff_value, weight='weight')

print("Dijkstra's shortest path from node 0:", path)
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