Inter-rater reliability of the pharmacists' assessment using the causality algorithms was 0.75.
The use of causality theory allows experts to quantify their knowledge and beliefs regarding the effectiveness of organizational strategies.
Put differently, and more boldly, their use of causality was not supported by an adequate theory of causality.
The causality algorithms were used to standardize the pharmacists' assessments, and to ensure that the exacerbation of underlying disease was considered as a cause for any events deemed potentially due to an adverse drug event.
As an alternative to classic potential causality, we advocate the use of explicit causality, or application-defined happens-before relations.
For a front propagation method to perform efficiently, the algorithm must make use of the causality information embedded in the problem.
I illustrate the use of these causality interfaces to statically analyze timed models and synchronous language compositions for causality loops and dataflow models for deadlock.
We illustrate the use of these causality interfaces to statically analyze timed models and synchronous language compositions for causality loops and dataflow models for deadlock.
We illustrate the use of these causality interfaces to statically analyze discrete-event models for uniqueness of behaviors, synchronous models for causality loops, and dataflow models for schedulability.
The equivalent stresses are derived with the use of the causality principle.
