  This report presents the evaluation approach developed for the DARPA Big
Mechanism program, which aimed at developing computer systems that will read
research papers, integrate the information into a computer model of cancer
mechanisms, and frame new hypotheses. We employed an iterative, incremental
approach to the evaluation of the three phases of the program. In Phase I, we
evaluated the ability of system and human teams ability to read-with-a-model to
capture mechanistic information from the biomedical literature, integrated with
information from expert curated biological databases. In Phase II we evaluated
the ability of systems to assemble fragments of information into a mechanistic
model. The Phase III evaluation focused on the ability of systems to provide
explanations of experimental observations based on models assembled (largely
automatically) by the Big Mechanism process. The evaluation for each phase
built on earlier evaluations and guided developers towards creating
capabilities for the new phase. The report describes our approach, including
innovations such as a reference set (a curated data set limited to major
findings of each paper) to assess the accuracy of systems in extracting
mechanistic findings in the absence of a gold standard, and a method to
evaluate model-based explanations of experimental data. Results of the
evaluation and supporting materials are included in the appendices.
