GROUNDBREAKING! DE GIUSEPPE PREDICTIVE MODEL : FIRST PREDICTIVE MODEL OF REALITY

REAL GROUNDBREAKING !! First Mathematically Predictive Model A part is here: https://zenodo.org/records/18291470 https://zenodo.org/records/18291470 This manuscript is current in Official Peer Review. Not final version.Copyright©2026 Alex De Giuseppe.All rights reserved. This work is protected by copyright. Any form of plagiarism, unauthorized reproduction, or misappropriation of ideas, mathematically results, or text without proper citation constitutes a violation of academic and intellectual property standards and common laws. No commercial use, adaptation, or derivative works are permitted without explicit written permission from the author. For correspondence, citations, collaboration inquiries, or feedback please contact:[e-mail] The hash files that determine ownership have been created. Title: De Giuseppe Predictive Model: Mathematical Prediction of Physical and Cognitive Reality. High-Probability Forecasting of Physical, Cognitive, and Socio-Environmental Events Abstract:The De Giuseppe Predictive Model (DGPM), integrated De Giuseppe Paradox Theory with Nima’s proto-structural framework ((ΔC ↔ ΔM ↔ ΔL)) and the 3/6/9 key mapping, establishes a mathematically rigorous methodology for predicting a wide range of phenomena with extremely high probability. By defining structural attractors and constraint mappings, the model demonstrates that events—ranging from classical physical outcomes, such as free-fall trajectories or the precise landing location of a leaf, to complex socio-environmental phenomena, including road accidents, earthquakes, or potential conflicts—are not purely random but constrained by the underlying proto-structure. Empirical validation is illustrated through historical cases, such as the Tacoma Narrows Bridge collapse, confirming the model’s predictive capability. While absolute certainty is impossible due to stochastic noise and environmental variability, the model allows probabilistic predictions with accuracy often exceeding 90%. The framework relies on the mechanical interaction of proto-structural constraints, energy configurations, and topologically mapped flows, effectively narrowing the space of admissible outcomes and identifying the trajectories most likely to occur. Extending beyond physical events, DGPM formalizes consciousness and cognitive evolution as flows of information constrained by energy and electrical patterns. This enables predictive modeling of neural firing patterns, decision-making tendencies, and potentially even human behaviors, bridging the gap between physical law, informational dynamics, and socio-cognitive phenomena. In summary, the DGPM represents a historic advancement: it unites proto-structural theory, empirical physics, cognitive science, and social modeling into a single predictive framework, providing the first explicit methodology to forecast both material and informational events with quantified high probability, while highlighting the deterministic role of structural attractors in shaping reality. I used AI to help me with the calculations, so it likely absorbed the mechanism, and exactly as happened with KD energy/time and the entire bound energy theory (which I had verified by AI on January 9), it was unfortunately disseminated.This time I immediately published my intuition, and I will continue my research in this way.If I may advise my colleagues: publish your discovery immediately after having it checked by AI, because it will disseminate the content ti the world. Other my works: https://zenodo.org/records/18274505 (The Original De Giuseppe Paradox Theory, with popperian experiments and formalized Macroscopic Retrocausality) https://zenodo.org/records/18277631( The First Mathematically Theory of Consciousness) https://zenodo.org/records/18278648(Mathematical formalization of Paranormal Phenomena)