A Comparative Analysis of the Outputs of Gemini and ChatGPT Systems in the Design of Specialized Nutrition for Futsal Players in Light of the Requirements of the Local Environment

Abstract

The aim of the present research was to conduct a comparative evaluation between the outputs of the artificial intelligence (Gemini) and (ChatGPT) systems to determine their accuracy and reliability in designing specialized sports nutrition programs for futsal players (for the category under 18 years old), and the extent to which these systems respond to the requirements of the local environment in the city of Najaf. The researcher used the descriptive method with the analytical method to suit the nature of the study, and the research sample was represented in the (Gemini) and (ChatGPT) systems as smart software tools. To achieve the objectives of the research, the researcher prepared a "scientific evaluation form" that was presented to (5) experts specialized in sports nutrition and physiology, which included (8) specialized evaluation axes.

After statistical processing of the data using arithmetic mean, relative weight, and T-test  of correlated samples, the results showed that both systems have a high ability to design nutrition programs with a general relative weight of more than (83%). The value of the significance level (Sig)  also appeared to be lower than the significance level (0.05), which indicates that there are significant differences between the two systems and in favor of  the (Gemini) system, which achieved a calculated  value of (T) of (3.32). Gemini has clearly excelled in taking into account the environmental variables of the city of Najaf and the timings of meals associated with hospitalization. The researcher concluded that  the  Gemini system is the most efficient in providing "environmental"  nutritional solutions that suit the specificity of the Iraqi player, and recommended the need to adopt these technologies as auxiliary tools under specialized supervision to ensure scientific safety.