Davini Zero-Contradiction Law: Cross-Domain Validation and Functional Equilibrium Dataset

This dataset consolidates the analytical, numerical, and applied validations of the Davini Zero-Contradiction Law (ZC Law), establishing ZC* ≈ 0.64 as a universal equilibrium ratio linking order and randomness. The collection spans physical (energy dissipation → coherence), biological (heart rate variability), informational (queue and epidemic models), and artificial (learning and AI training curves) domains. All systems converge to the same coherence constant within experimental precision. This archive includes cross-domain simulation logs, code excerpts, and raw time-series files supporting the claim of a domain-agnostic functional law of equilibrium.本数据集整合了针对达维尼无矛盾定律（Davini Zero-Contradiction Law，简称ZC定律）的分析、数值与应用验证，确立ZC*≈0.64作为连接有序性与随机性的通用均衡比率。该数据集涵盖物理（能量耗散→相干性）、生物（心率变异性）、信息（队列与流行病模型）以及人工（学习与AI训练曲线）领域。所有系统在实验精度范围内均收敛至同一相干性常数。本归档包含跨域仿真日志、代码片段与原始时间序列文件，用以支撑该无领域限制的通用均衡函数定律的相关论断。