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This paper examines the interdependence generated between two parent nodeswith a common instantiated child node, such as two hypotheses sharing commonevidence. The relation so generated has been termed "intercausal." It is shownby construction that inter-causal independence is possible for binarydistributions at one state of evidence. For such "CICI" distributions, the twomeasures of inter-causal effect, "multiplicative synergy" and "additivesynergy" are equal. The well known "noisy-or" model is an example of such adistribution. This introduces novel semantics for the noisy-or, as a model ofthe degree of conflict among competing hypotheses of a common observation.

"Conditional Inter-Causally Independent" Node Distributions, a Property of "Noisy-Or" Models