Within the realms of workflow management and grid computing, scheduling of distributed services is a central issue. Most schedulers balance time and cost to fit within a client's budget, while accepting explicit data dependencies between services as the best resolution for scheduling. Results are extracted from one service in total, and then simply forwarded to the next service. However, distributed objects and remote services adhere to various standards for data delivery and result extraction. There are multiple means of requesting results and multiple ways of delivering those results. By examining several popular and idiosyncratic methods, we have developed a comprehensive model that combines the functionality of all component models. This model for arbitrary result extraction from distributed objects provides increased flexibility for object users, and an increased audience for module providers. In turn, intelligent schedulers may leverage these result extraction features. Key...