1. Ground truthing2. Experiment design3. Meta-Analytic design patterns4. Sensitivity analysis and big system engineering5. Multi-path predictive selection6. Modeling and model fitting: including Antibody model, stem-differentiated cell model, and chemical, physical and environmental models for greater diversity in form7. Synonym-antonym and Reinforce-Void patterns and their value in data consensus, data anonymization, and data normalization8. Meta-analytics as analytics around analytics (functional metrics, entropy, EM). Ingesting statistical approaches for specific domains and generalizing them for data hybrid systems9. System design optimization (entropy, error variance, coupling minimization F-score)10. Aleatory techniques/expert system techniques.tie to ground truthing and error testing11. Applications: machine translation, robotics, biological and social sciences, medical and healthcare informatics, economics, business and finance12. Discussion and Conclusions, and the Future of Data