okay is this a research paper if so give... - tlooto, The Most Powerful AcademicGPT

Yes, this is a peer-reviewed research article that presents a rigorous proof-of-concept study on the use of artificial intelligence—specifically, neural network models—to estimate postharvest food losses (FL) at national and sub-national levels based on public secondary data sources. --- Models and Methods Used 1. Feedforward Neural Networks (FNNs) - Type: Standard data-driven multilayer perceptrons - Purpose: To predict national/sub-national postharvest food loss using only the available data, without explicit embedding of expert knowledge or rules. - Input Features/Predictors: (see Table 1, page 4) - FAO region (one-hot encoded) - Year - Population (in thousands) - GDP per capita - Precipitation (mm) - Protein supply (g/capita/day) - Production (1,000 tonnes) - Data Sources: FAO Food Balance Sheets, World Bank DataBank. - Training/Evaluation Procedure: - The dataset (1961–2020) is randomly split 50 times into training (80%) and testing (20%) sets to avoid random bias (Figure 2, page