ChatGPT-4o's responses were the most convincing due to the inclusion of more numerical values and forecasts than 3 Opus, while avoiding short bullet points with less substance associated with 3.5 Sonnet as seen in Figure . In general, all three models provided valuable insight regarding how LLMs can assist a single paper according to Figure . In addition, other authors' methods and results were found to be impactful towards assisting the primary paper being analyzed. For instance, Paper 02 weaknesses of interpretability and Qlac were believed to be improvable using natural language processing benefits, or soft sensor techniques by Liang et al. 3.5 Sonnet's results shown in Table shows strengths regarding insights in lactate shift mechanisms and citing numerical data in quotes, but had was less proficient in providing convincing author forecasts and breakthroughs, as shown for each condition in Table .