Modern systems are increasingly susceptible to soft errors in the field and traditional redundancy-based mitigation techniques are too expensive to protect against all errors. Recent techniques, such as approximate computing and various low-cost resilience mechanisms, intelligently trade off inaccuracy in program output for better energy, performance, and resiliency overhead. A fundamental requirement for realizing the full potential of these techniques is a thorough understanding of how applications react to errors. Approxilyzer is a state-of-The-Art tool that enables an accurate, efficient, and comprehensive analysis of how errors in almost all dynamic instructions in a program's execution affect the quality of the final program output. While useful, its adoption is limited by its implementation using the proprietary Simics infrastructure and the SPARC ISA. We present gem5-Approxilyzer, a re-implementation of Approxilyzer using the open-source gem5 simulator. gem5-Approxilyzer can be extended to different ISAs, starting with x86 in this work. We show that gem5-Approxilyzer is both efficient (up to two orders of magnitude reduction in error injections over a naive campaign) and accurate (average 92% for our experiments) in predicting the program's output quality in the presence of errors. We also compare the error profiles of five workloads under x86 and SPARC to further motivate the need for a tool like gem5-Approxilyzer.