Introduction: The recently validated Guide Against Age Related Disease (GARD) dietary screener quantifies diet and behavior using Assembly Theory. It has shown strong correlations with known dietary patterns. However, its predictive utility in active populations remains untested. We propose a computer model that integrates GARD scores with a novel Safety and Reciprocity Quotient (SRQ)—a proxy for perceived life stress and environmental threats—to explain variability in weight loss and recovery under a consistent caloric deficit for patients trying to lose weight.

Methods: In a retrospective chart review, we plan to validate the model by evaluating patients enrolled in a diet and exercise program. Diet will be measured using the GARD screener (validated in Nutrients, 2025), and psychological safety will be estimated using the SRQ, derived from Adverse Childhood Event (ACE) scores, social determinants, and the Holmes–Rahe stress inventory. Our thermodynamic computer model treats the body as a heat engine with energy flows allocated first to basal metabolism, then to somatic activity (exercise), and then healing vs storage. High SRQ scores will bias energy flow to storage over healing and recovery.

Results: We hypothesize that patients with high GARD scores and low SRQ will exhibit persistent weight loss and exercise habits, while those with low GARD or high SRQ will exercise less frequently and show plateauing weight loss despite caloric restriction. We expect the combined GARD–SRQ model to outperform caloric balance models in predicting longitudinal weight changes and recovery.

Conclusions: This study aims to validate the Human Heat Engine, a predictor of metabolic resilience and weight trajectory combining dietary measurement with stress metrics. Our findings may support a shift toward personalized interventions in metabolic health and exercise recovery.