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Modeling causality is complicated work.
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Granger causality is another exploratory, data-driven modeling technique that has been particularly popular due to its promise of identifying causal relationships between nodes based on temporal lags between them [ 41].
Causality is always difficult to establish.
The causality is pretty straightforward.
Such a mode of causality is called 'univocal causality'.
Causality is the most obvious case (A.24e).
Establishing causality is always a challenge.
But if it's only 30 minutes later, the causality is pretty inarguable.
Whether you want to claim coincidence or causality is up to you.
This implies that the construct "causality" is very abstract.
#Causality is abandoned.
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