For Part II, ChatGPT-4o provided a detailed report regarding how certain extracellular metabolites or extracellular metabolite relationships were improved by document retrieval of Sukwattananipaat, P., et al., 2024. The large auto-scaled LC-MS 136 extracellular metabolite table combined with the ChatGPT-4o report and a detailed prompt were processed by each of the six LLMs, yielding a new abbreviated table with LLM forecasted values. This revised table was then combined with a 10 paper summary, and an additional review summary with a prompt requesting how a LLM or any of the authors' findings in the study can be used to improve metabolite relationships. Original o1-preview values typically reflected the author's table amongst many values checked, however one incorrect value was found. o1-preview was superior in answering each of the four conditions judged by the manuscript author. Due to the complexity of the table and the additional pieces of information needed for processing, models typically chose to return either a portion of the metabolites under study before timing out, or included a portion of unchanged metabolite forecasts with all metabolites expected to see improvements (o1-preview). For 3 Opus, the AI software listed as many forecasts as it could before ending at 91 metabolites. o1-preview, however, included metabolites it believed would see breakthroughs due to other authors' methods, while other unchanged values were not included due to processing restrictions.