Exactly. In some cases disease causes death. In others it causes immunity which in turn causes “good health” and postpones death.
Exactly. In some cases disease causes death. In others it causes immunity which in turn causes “good health” and postpones death.
Contradictory cause-effect examples, each backed up with data, are a reliable indicator of a class of situations that need a higher chain-effect resolution.
Which is directly usable knowledge if you are building out a causal graph.
In the meantime, a cause and effect representation isn't limited to only listing one possible effect. A list of alternate disjoint effects, linked to a cause, is also directly usable.
Just as an effect may be linked to different causes. Which if you only know the effect, in a given situation, and are trying to identify cause, is the same problem in reverse time.
It is my opinion that if we examine any factor closely, it will have multiple disjoint effects. As in nothing is absolutely unilateral in its effects. Some of those effects will depend on certain conditions. If it is possible to specify condition, annotations, and other nuances such as levels of confidence or source of the opinion, such a database might be pretty useful.