An auditable consensus workflow around four causal-discovery methods gives higher-precision links on synthetic benchmarks, but the precision gain disappears on a real river network where the reference graph is incomplete.
Springer, Berlin, Heidelberg
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AutoCause: A Python framework that automates expert decisions in environmental time-series causal discovery
An auditable consensus workflow around four causal-discovery methods gives higher-precision links on synthetic benchmarks, but the precision gain disappears on a real river network where the reference graph is incomplete.