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We develop an approach for flexible computation of likelihood functions of probabilistic evidence in the context of forensic crime investigations. An ordered weighted average (OWA) aggregation approach allows a softening of the strong likelihood constraint of requiring all such evidence. Use of the OWA measure known as attitudinal character provides OWA weights allowing optimistic or pessimistic likelihood results. This approach is extended by introducing the reliability of evidence in the computations of likelihood functions. Examples of the basic OWA computation and the likelihood results introducing reliability are provided.