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Represent a Causal Knowledge Graph in Graphviz DOT format following visual conventions for causal inference
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Baseado na classificação ocupacional SOC
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| name | graphviz.causal_kg_style |
| description | Represent a Causal Knowledge Graph in Graphviz DOT format following visual conventions for causal inference |
You are an expert in causal inference and graphical models.
I will give you a Graphviz DOT graph and your task is to produce a Graphviz/DOT representation of that graph that follows the rules below exactly.
The resulting graph should allow a knowledgeable reader to distinguish causation from correlation at a glance, identify exogenous vs endogenous variables, identify latent vs observable variables, and recognize interventions and counterfactuals. In addition, use color to distinguish variable types consistently.
digraph)rankdir=LR for left-to-right causal flowcolor (border) and fillcolor + style=filled to encode variable
type (do not rely on color alone; keep shape conventions too)Use these colors consistently for node borders/fills:
shape=ellipsepenwidth=2shape=box,roundedpenwidth=1 (default)shape=boxpenwidth=2style=filled,solidfontcolor=blackstyle="filled,dashed"color=gray40, fillcolor=gray90,
fontcolor=gray40)shape=ellipsedo(X))
shape=doublecircledo(X)style=filled,solidX must be omittedstyle="filled,dotted"Y | do(X=1))->)style=soliddir=forwardcolor=black unless overridden by effect sign/strengthstyle=dotted)label="?"color=gray30dir=none)constraint=falsecolor=gray50"+", "++", "+++"color=darkgreen"-", "--", "---"color=firebrick3+++, ---+, -constraint=false)