"How can monoclonal antibody continuous production numerical data in this article be improved through the incorporation of Large Language Model integrated problem solving (monte carlo simulations, markov chain models, etc.)? Identify the selections of numerical data from the article in quotations and also provide updated numerical data, not percent increases, that LLMs will yield based on speed or performance." Prompt B referenced Large Language Model integrated problem solving methods such as monte carlo simulations and markov chain models that would improve monoclonal antibody continuous production numerical data found in five articles seen in Table . The "Original Numerical Data" column in the table generated by ChatGPT-4o matched values found in the articles, except in one case for "N-Glycosylation (G2FS2 Glycan Type) 8.70%, which should instead be listed as "G2 Type" from Liang, G., et al.